The Effect of VAT Threshold on the Behavior of
Small Businesses: Evidence and Implications
Jarkko Harju, Tuomas Matikka and Timo Rauhanen
The Eect of VAT Threshold on the Behavior of Small
Businesses: Evidence and Implications
∗
Jarkko Harju, Tuomas Matikka and Timo Rauhanen
March 30, 2015
Preliminary version
Abstract
Small businesses are often regarded as important determinants of economic growth. Simultaneously, many tax rules and regulations are size-dependent, which might decrease eciency and the
economic activity of growing rms. We study the eects of the value-added tax (VAT) threshold on
the behavior of small businesses. In Finland, rms with annual sales below 8,500 euros are not liable
to pay VAT. We use detailed register data on the universe of Finnish businesses and the bunching
method to provide robust and clear evidence of behavioral eects of the threshold. We nd that
the VAT threshold has notable eects among small business. Firms bunch actively just below the
threshold, which implies notable eciency implications. We nd that changing tax incentives at the
threshold does not have a signicant eect on the extent of the response. This implies that compliance costs are important in explaining observed responses. We nd no evidence of tax avoidance or
evasion, which suggests that rms respond by reducing output. Also, we nd that bunching behavior
is relatively permanent, which implies that the threshold decreases the growth of small businesses.
Keywords: Small businesses, value-added tax, VAT threshold, bunching
JEL codes: H21, H25, H32
∗ Government
Institute
Timo.Rauhanen@vatt.
for
Economic
Research
VATT.
1
Jarkko.Harju@vatt.,
Tuomas.Matikka@vatt.,
1
Introduction
Small and especially young businesses are often regarded as important determinants of economic growth
(see e.g. Haltiwanger et al. 2013, Decker et al. 2014). Simultaneously, many tax rules and regulations
are size-dependent. These rules might reduce the eciency of taxation and decelerate economic activity,
in contrast to widespread objectives to enhance the growth of small businesses.
Value-added tax (VAT) is a commonly applied form of consumption taxation, and a crucial component
of tax revenue in many countries. Most VAT systems include varying thresholds below which rms are
exempt from remitting VAT. For example, in the EU, VAT threshold varies between 0-100,000 euros.
Despite the potential detrimental eects of size-dependent thresholds, there is only limited evidence on
the eects of VAT threshold on the behavior of small businesses.
In Finland, rms with annual sales below 8,500 euros are not liable to pay VAT and separately report
sales to the Tax Administration. Relatively low VAT thresholds are common. Half of the EU countries
apply thresholds below 25,000 euros, including for example Germany, Belgium and Denmark. In general,
small rms comprise a large share of all businesses. In Finland, one third of all registered rms have
turnover below 25,000 euros. Among young and potentially growing rms, the share of businesses with
small turnover is even larger. Over 40% of rms that are younger than three years have turnover below
25,000 euros.
In this study we present comprehensive evidence on the eects of the VAT threshold among small
businesses. We utilize detailed data on the universe of Finnish businesses, including also rms below the
VAT threshold. We use the bunching method in order to provide clear and robust evidence on behavioral
eects.
To understand the implications of the VAT threshold, it is important to know both why and how
rms respond to it. By utilizing changes in VAT rules at the threshold, we analyze the role of both tax
incentives and compliance costs. We study the anatomy of the response to learn whether rms react by
changes in real economic activity or by tax avoidance and evasion. In order to illustrate the important
dynamic aspects of the VAT threshold, we analyze how the threshold aects growth and development of
small businesses.
First, rms could respond to the VAT threshold both because of increased taxation and increased
compliance costs above it. We utilize variation in tax incentives and compliance costs to analyze why
rms react to the threshold.
Before 2004, VAT liability increased sharply at the threshold, as rms
marginally above the threshold were liable to fully pay the VAT on all sales. In 2004, Finland introduced
a VAT relief scheme, in which remitted VAT increases gradually above the threshold. Thus the reform
drastically changed tax incentives at the threshold, which allow us to disentangle the eects of tax
incentives and compliance costs.
Second, rms can respond to the threshold by reducing sales, or by engaging in various tax avoidance
activities or underreporting of sales. We analyze the nature of the response by studying how the production factors of the rms, such as equity and expenses, develop around the VAT threshold. Potential
discontinuous changes in production factors exactly at the VAT threshold indicate changes in behavior
caused by this regulation, and shed light on how rms respond to the threshold.
Third, in terms of welfare eects, it is essential to know how the VAT threshold aects the growth of
small businesses. The threshold could signicantly hinder growth if rms avoid exceeding the threshold
for a prolonged period of time. The panel structure of the data allow us to follow rms over time, which
enable us to characterize the eect of the threshold on growth and the scale of business activity.
We nd that the VAT threshold has notable eects among small business.
just below the threshold, which implies signicant eciency implications.
Firms bunch actively
We nd that changing tax
incentives at the threshold does not signicantly decrease the eect, which implies that compliance
costs are important in explaining observed behavior.
We nd no clear evidence of tax avoidance or
evasion, which suggests that rms respond by changes in real economic activity. Finally, we nd that
2
bunching behavior is relatively permanent, which implies that the threshold decreases the growth of
small businesses.
Despite the scal importance of VAT and the generally applied sales thresholds, only a few previous
papers study the eects of these thresholds. The theoretical literature has focused on determining the
rules for optimal VAT threshold. Keen and Mintz (2004) and Kanbur and Keen (2014) show that the
optimal VAT threshold depends on administrative and compliance costs, and the extent of the eect of
the threshold on rm behavior. Empirically, Onji (2009) was the rst to detect clear eects of the VAT
threshold on the distribution of rms in Japan. He shows that relatively large Japanese rms reacted
to the introduction of a VAT threshold by splitting into smaller entities, reecting clear tax avoidance
behavior. Li and Lockwood (2014) show that rms in the UK bunch actively at the relatively large VAT
threshold (approx.
¿90,000).
Also, Waseem (2015) observes a strong clustering of rms at the VAT
threshold in Pakistan.
This paper proceed as follows: Section 2 describes the VAT system and the VAT threshold in Finland.
Section 3 presents the methodology and Section 4 describes the data. Section 5 oers the results and
Section 6 concludes the study.
2
Institutions
2.1 Value-added taxation
Most developed countries use the value-added tax (VAT) as their primary consumption tax system. VAT
is usually a broadly based tax assessed on the value added to goods and services. The amount of value
added is calculated by subtracting the amount of externally purchased goods and services from the value
of goods and services produced.
In short, the VAT assessment process is the following:
each trader in the chain of supply from
manufacturers to retailers charges VAT on the sales. Firms are entitled to deduct from this amount the
VAT paid on purchases. VAT is remitted to the tax authorities by the seller of the goods and services.
VAT is the main source of tax revenue in many developed countries. For example, among all OECD
countries almost one-fth of all tax revenue is collected by VAT. However, the variation in VAT revenues
is large across countries.
A common feature in many VAT systems is that rms with annual sales under a certain threshold
are not required to register and remit VAT. Figure 1 depicts these annual sale thresholds among OECD
countries in 2014. The Figure shows thresholds vary notably across countries. While some countries levy
VAT on all turnover without any threshold (e.g. Sweden and Turkey), some countries apply relatively
high thresholds around 100,000 euros (e.g. Switzerland and the UK).
2.2 VAT in Finland
Finland, as a member of the EU, applies the general EU VAT legislation. All members of the EU apply
a standard rate of at least 15%. The EU allow member countries to use a maximum of two reduced VAT
rates for specic products and services, such as food and pharmaceuticals.
The standard VAT rate in Finland is 24% in 2014 that applies to most of the goods and services sold.
Finland uses two reduced rates: 14% is applied to e.g. food and restaurant services, and 10% is applied
to e.g. books and pharmaceuticals.
VAT registered rms are obliged to regularly le periodic tax returns to the Finnish Tax Administration. The ling and reporting obligation covers all VAT on sales at dierent rates, input purchases,
zero-rated sales, imports and exports.
The frequency of the required reports depends on the annual
sales of a rm: Firms with annual sales below 25,000 euros are allowed to report annually, rms with
3
VAT thresholds in OECD countries in 2014 (in euros)
Chile
Mexico
Spain
Sweden
Turkey
Netherlands
Greece
Belgium
Norway
Iceland
Denmark
Finland
Portugal
Estonia
Israel
Germany
Hungary
Korea
Canada
Luxembourg
Average
Austria
Italy
Poland
Czech Republic
New Zealand
Slovak Republic
Slovenia
Australia
Japan
Ireland
France
Switzerland
United Kingdom
0
20,000
40,000
60,000
Sales (in euros)
80,000
100000
Source: OECD Statistics
Figure 1: Annual sale thresholds for VAT registration among OECD countries in 2014 (in euros)
turnover 25,000-50,000 euros must report quarterly, and rms with sales above 50,000 euros have to
report monthly.
Some sectors and industries are exempt from VAT or have other special rules for paying VAT. These
include nancial and insurance activities, letting and operation of dwellings, education, human health
and social work activities. A rm that sells solely these goods or services are not liable to pay VAT.
VAT threshold before 2004.
In Finland, the VAT threshold for rms is 8,500 euros of annual sales.
Below this threshold rms are exempt from VAT. The threshold has remained constant from 1995, even
in nominal terms. Albeit small businesses below the threshold are exempted from VAT, they need to pay
other taxes and report their income to the Tax Administration. Firms that exceeded the threshold paid
VAT for sales, including sales below the threshold. Thus the average tax rate jumps at the threshold
before 2004.
Firms that do not exceed the thresholds can voluntarily register and pay VAT. There are logical
reasons for registering even when it is not necessary. A rm can only deduct VAT from purchases and
costs if registered. For example, voluntary registration could be important for businesses that have large
start-up costs. Also, rms below the threshold that have a large share of business-to-business sales have
an incentive to register, as the VAT rebate is only possible from purchases of VAT registered rms.
VAT relief scheme from 2004 onwards.
The VAT rate at the threshold changed in 2004 although
the threshold itself remained at 8,500 euros. The reform introduced a VAT relief scheme for annual sales
below 20,000 euros in 2004 and 22,500 euros 2005 onwards. After the reform, rms can apply for a VAT
relief that gradually decreases (above 8,500 euros) with the increase in sales.
Figure 2 shows the VAT remittance (above) in euros and average tax rates (below) for dierent levels
of total annual sales of rms for dierent years. The data is split to 100 euro turnover bins in the Figure.
The Figure shows the introduction of the relief region in 2004 and post-2005 in comparison to pre-2003
4
period for a representative rm that is subject to the standard VAT rate.
The Figure clearly depicts that the pre-reform system created a salient VAT notch, implying a jump
in remitted VAT and the average VAT rate from 0 to 22% at the threshold (standard VAT was 22% rate
in 2003-2009 in Finland). After the reform the notch was replaced by a VAT kink, implying a gradually
increasing remitted VAT and average VAT rates above the threshold. Within the relief scheme, gradually
increasing average VAT rate implies an increasing marginal VAT rate up to the point in which the average
VAT rate equals 22%. This leads to marginal VAT rates between 13-57% within the relief region, which
was 8,500-20,000 euros in 2004 and 8,500-22,500 euros from 2005 onwards.
An additional important detail of the VAT relief is that it is not automatically granted by the Tax
Administration. Firms needed to apply for the VAT relief using a separate tax form before 2010. From
2010 onwards, rms can apply for the VAT relief with the same periodic tax form they use to declare
VAT. This can have important implications for the salience of the VAT relief.
Remitted VAT and average tax rates before and after the reform
0
Remitted VAT
3000 6000
Remitted VAT
0
5000
10000
15000
20000
25000
30000
20000
25000
30000
Average tax rate (%)
0 5 1015202530
Average tax rates
0
5000
10000
15000
Annual turnover
VAT pre−2003
VAT post−2005
VAT 2004
Figure 2: VAT remittance and average VAT rates for dierent levels of sales before and after the introduction of VAT relief region
3
Methodology
3.1 Bunching at the VAT threshold
We use the bunching methodology introduced in Saez (2010) to analyze responses to the VAT threshold.
The intuition behind the bunching approach is that if a discontinuous change in tax liability at the
threshold aects the behavior of rms, we should nd an excess mass of rms located at the threshold.
Consider a rm which is owned and managed by a single entrepreneur
1
that maximizes the following
function
1 As the VAT threshold in Finland is low, most rms around it are managed and owned by a single owner. Therefore,
it is reasonable to assume that individual owners make the relevant decisions on s. However, for conceptual simplicity,
throughout the paper we denote that rms respond to the VAT threshold, not individual owners.
5
π = (s − d(s))(1 − τp ) − c(s) − τvat d(s) − [T (s)vat − τvat d(s) + δ(s)] · 1(s > s∗ )
where
s
denotes annual sales, and
d(s)
(1)
is a concave funtion of tax-deductible costs needed to generate
s.
We assume that the marginal unit of sales produces positive net income for the rm, which implies that
d0 (s) ≤ 1.
Net income from the rm
(s − d(s))
is taxed at a at income tax rate
function of the cost of eort of the owner, which is not tax-deductable.
where
τvat
T (s)vat
denotes the at VAT rate.
τ vat d(s)
τp . c(s)
is a convex
is VAT paid on
denotes the convex VAT function, and
δ(s)
d(s),
represents
compliance costs related to VAT reporting.
The rm is not liable to report and pay VAT below a sales threshold
0
if
∗
s≤s
, and thus exceeding
∗
s
s∗ .
Therefore,
[T (s)vat − τvat d(s) + δ(s)] =
creates a jump in both remitted VAT and compliance costs. However,
above the threshold the rm can deduct the VAT on tax-deductible costs from remitted VAT. Below
s∗
VAT paid on purchases is not tax-deductable.
(s∗ −,s∗ ) below the VAT threshold.
0
0
0
Maximizing π with respect to s below the threshold implies that c (s) = (1 − d (s))(1 − τp ) − τvat d (s).
∗
0
0
0
0
At s , maximization yields c (s) = (1 − d (s))(1 − τp ) − T (s)vat − δ (s). Let us assume that d(s) is
∗
∗
0
approximately linear in sales within (s − ,s ), which implies that d (s) is approximately equal within
Let us consider rm decision making within a small sales interval
this region. Firms have incentives not to exceed the threshold because the marginal cost of additional
sales is larger at the threshold than just below it,
τvat d0 (s) ≤ T 0 (s)vat + δ 0 (s).
Intuitively, an additional
unit of sales is less valuable at the VAT threshold because the rm needs to pay both VAT and compliance
costs if
s∗
is exceeded.
First, we study the eect of the change in the VAT rate at the threshold. For now we ignore compliance
costs, which we will study in Section 3.3. In Finland, there has been two kinds of changes in the VAT
rate at the threshold: a VAT notch and a VAT kink.
To start with the VAT notch, consider a VAT
schedule where sales are not taxed until the notch point
s∗ .
applied to all sales. Thus the VAT liability jumps discretely at
the sales below
s∗
If sales exceed
∗
s
s∗ ,
the VAT rate will be
, as the rm needs to pay VAT also for
if the threshold is exceeded. More formally, the VAT function in equation (1) in the
notch schedule is of the form
Tvat = s ∗ τvat · 1(s > s∗ ),
where
τvat
is the at VAT rate.
Bunching behavior at the VAT notch is illustrated in the upper graph of Figure 3.
The vertical
axis denotes the net-of-tax sales, and horizontal axis denotes sales before taxes. The straight blue lines
illustrate the tax rates, and curvy red lines the indierence curves of dierent rms (type A and type
B).
4τvat
represents the VAT paid from sales below the threshold once the VAT threshold is exceeded.
A fraction of rms originally above
s∗
will locate themselves at the VAT threshold after the introduc-
tion of a discontinuous jump in VAT liability. The extent of this bunching behavior depends on the sales
elasticity with respect to VAT rate, which we will come back to in more detail below. Firms originally
at
s∗
or below the threshold will not change their behavior after the introduction of the notch (type
A rm).
In the graph,
s∗ + 4s
denotes the hypothetical rm with the highest sales to bunch at the
threshold (type B rm). In other words,
s∗ + 4s
marks the last rm bunching at the notch, which we
call the marginal buncher. More formally, the fraction of rms located at
is denoted as
B(∆s) =
´ s∗ +∆s
s∗
h0 (s)ds,
where
h0 (s)
absence of the notch.
6
s∗
in response to the notch
denotes the counterfactual density of sales in the
Indifference
curves
Net-of-tax
sales
Type B
Type A
Slope (1-τp- τvat)
∆ τvat
Slope (1-τp)
sB s*+∆s
s*
sales
Indifference
curves
Type B
Net-of-tax
sales
Type A
Slope (1-τp- τvat)
Slope (1-τp)
s*
s*+∆s
sales
Figure 3: Bunching at a VAT notch (upper graph) and a VAT kink (lower graph)
Bunching at the VAT kink is illustrated on the lower graph side of Figure 3. In the VAT kink system,
s∗ are taxed at the VAT rate, and the VAT function in equation (1) is of the form
Tvat = (s − s ) ∗ τvat · 1(s > s∗ ). Type A rm which is located at s∗ before the introduction of the
∗
VAT kink will not respond to the kink, whereas a fraction of rms above s will locate themselves at the
only sales exceeding
∗
VAT kink. As with notches, type B rm in the graph represents the marginal rm with the largest sales
∗
(s
+ 4s)
to bunch at
s∗
after the introduction of the VAT kink.
Intuitively, the main dierence between VAT notch and VAT kink is the size of the change in tax
7
incentives at the threshold. Compared to VAT notch, a VAT kink produces notably smaller incentives to
respond. Therefore, it is presumable that less rms will bunch at the VAT kink than at the VAT notch.
Figure 4 describes bunching in the sales distribution.
In the Figure, the horizontal axis denotes
the number of rms and vertical axis denotes sales levels. The solid blue line represents observed sales
distribution, and the dotted red line the counterfactual density in the absence of the threshold.
excess mass caused by the threshold is presented as a spike in the distribution at
∗
s
∗
s
The
. The excess mass at
comes from the missing above the threshold. The missing mass above the threshold is denoted as the
area between the counterfactual distribution and the obseved distribution within the region
(s∗ , s∗ +4s).
Assuming smooth and heterogenous sales elasticities across dierent rms, the observed density gradually
approaches the counterfactual density above
s∗ .
Thus
s∗ + 4s
represents the rm with the largest sales
to bunch at the threshold. Intuitively, the larger the excess mass at the threshold is the further away
from
s∗ comes
the last rm to bunch at the VAT threshold. We discuss the empirical estimation in more
detail below.
Number of
firms
Excess mass
Observed
distribution
Counterfactual
Missing
mass
s*
s*+∆s
Sales
Figure 4: Bunching at the VAT threshold
Abstracting from compliance costs, there are also circumstances in which a rm has no tax incentive
to bunch at the VAT threshold.
The main instance is substantial VAT paid on purchases stemming
from, for example, large start-up costs. In other words, for some rms it could be that
T (s) < τvat d(s)
above the VAT threshold, and thus (marginally) exceeding the threshold does not increase tax liability.
d0 (s) > 1
Second, it could be that
for some small businesses in the short run, which might not induce
incentives to bunch at the threshold as
τvat d0 (s) > T 0 (s).
However, small businesses in our data are on
average protable and have notably larger level of sales compared to overall expenses, which indicates
that incentives to bunch at the VAT threshold exist for a large proportion of small rms in Finland.
3.2 VAT rate elasticities based on observed bunching
We approximate the sales elasticity at the VAT threshold using a similar approach as Kleven and Waseem
(2013). We characterize the elasticity at VAT notch and VAT kink by relating the earnings response of a
∗
marginal buncher rm (s
+ ∆s)
to the change in tax liability caused by exceeding the threshold by
8
∆s.
This upper-bound reduced-form approximation of the sales elasticity oers a conveivable way to scale
the extent of the behvioral response to the threshold with the change in the VAT rate under dierent
VAT rate schedules.
Elasticity at the VAT notch is calculated with the following quadratic formula
eN ≈ (4s/s∗ )2 /4tN
(2)
4tN = (4s + s∗ )τvat /4s denes the relative increase in VAT payments caused by exceeding the
threshold by ∆s. Importantly, when exceeding the VAT notch, the rm needs to pay VAT also for sales
∗
below s .
where
Sales elasticity associated with VAT kink can be written as
eK ≈ (4s/s∗ )2 /4tK
(3)
4tK = (4s)τvat /4s = τvat . Compared to the VAT notch, the rm needs to pay VAT only for
∗
sales above s within the VAT kink system, and thus the denominator of equation (3) reduces to the at
where
VAT rate.
Equations (2) and (3) imply that the change in the implicit marginal tax rate (4tN ,
at VAT notch compared to VAT kink.
4tK )
is larger
This is creates larger incentives to bunch at the VAT notch.
Therefore, assuming similar underlying (structural) elasticity regardless of the VAT system, we should
nd larger excess bunching at the VAT notch compared to the VAT kink.
3.3 Compliance costs of VAT reporting
[To be added here later]
3.4 Empirical analysis
The excess mass of rms at the VAT threshold is estimated by comparing the actual density function
around the threshold to an estimated smooth counterfactual density. The counterfactual density function
describes what the distribution of sales would have looked like without changes in tax liability at
We follow the methods in Chetty et al.
s∗ .
(2011) and Kleven and Waseem (2013) to estimate the
counterfactual density. Intuitively, the counterfactual density is estimated by tting a exible polynomial
function to the observed distribution, excluding an area around
we re-center income in terms of
∗
s
s∗
from the observed distribution. First,
, and group rms into small sales bins of 100
¿.
We estimate a
counterfactual density by regressing the following equation and excluding the region around the threshold
[sL , sH ]
from the regression
cj =
p
X
βi (sj )i +
i=0
In equation (4),
cj
ĉj =
Pp
i=0
p.
ηi · 1(sj = i) + εj
(4)
i=sL
is the count of rms in bin
of the polynomial is denoted by
sH
X
j,
and
sj
denotes the sales level in bin
j.
The order
Thus the tted values for the counterfactual density are given by
βi (sj )i .
The excess bunching is estimated by relating the actual number of rms close to the threshold within
(sL , s∗ ) to the estimated counterfactual density within the same region.
Ps∗
i=sL
b̂(s ) = P
s∗
∗
(cj − ĉj )
i=sL ĉj /Nj
where
Nj
is the number of bins within
[sL , s∗ ].
9
We calculate excess bunching as
(5)
One important question when estimating the counterfactual density is how to determine the excluded
the region
[sL , sH ].
As in earlier literature, we determine the lower limit
of the sales distribution. Intuitively,
sL
sL
based on visual observations
represents the point in the sales distribution where the bunching
behavior begins.
We follow the approach of Kleven and Waseem (2013) to dene the upper limit. We determine
Ps∗
such that the estimated excess mass b̂E (s ) = (
i=sL cj − ĉj ) equals the estimated
PsH
∗
the threshold, b̂M (s ) = (
s>s∗ ĉj − cj ). Theoretically, this condition denes that
∗
sH
missing mass above
rms who bunch at
the threshold come from the region directly above it. We apply this convergence condition by starting
from a small value of
sH
and increasing it gradually until
b̂E (s∗ ) ≈ b̂M (s∗ ).
This denition for
sH
denotes
the upper bound of the excluded range, and thus the lower bound for estimated excess bunching (Kleven
2
and Waseem 2013).
sales response
4s
In addition, the convergence condition implies that we can intuitively dene the
of the marginal buncher rm using the estimated excess mass and the upper limit
sH .
This enables us to approximate sales elasticities with respect to VAT rate for both the VAT kink and
the VAT notch by relating the marginal sales response to the implied change in the tax rate.
Following Chetty et al.
(2011) and Kleven and Waseem (2013), the standard errors for all the
estimates are calculated using a residual-based bootstrap procedure. We generate a large number of sales
distributions by randomly resampling the residuals from equation (4) with replacement, and generate a
large number of new estimates of the counterfactual density based on the resampled distributions. The
bootstrap procedure takes into account the iterative process to determine
sH .
Based on the bootstrapped
counterfactual densities, we evaluate variation in the estimates of interest. The standard errors for each
estimate are dened as the standard deviation in the distribution of the estimate.
4
Data and descriptive statistics
Our data are from the Finnish Tax Administration and contain all businesses that operate in Finland,
including rms that are registered to pay VAT and rms that are not included in the VAT register.
The data include all information needed for tax purposes, such as sales, number of employees, taxable
prots, total assets and organizational form.
Importantly, data include accurate information on total
sales also for rms below the VAT threshold. This enables us to analyze the eects of the VAT threshold
on the distribution of sales. In addition, we can link owner-level variables to the rm-level data, such as
personal taxable wage and capital income of the main owner of the rm.
Figure 5 shows the distribution of sales for all businesses with annual sales between 1,500-20,000
euros in 2000-2011. The Figure shows a clear excess mass at the VAT threshold of 8,500 euros (marked
with a vertical line in the Figure). This provides strong visual evidence that rms have responded to the
threshold. The distribution seem to be otherwise rather smooth, with the exception of round-number
bunching, which can be seen as spikes in the distribution at convenient round numbers such as 5,000,
10,000, and 15,000 euros. Nevertheless, bunching is much more evident at the VAT threshold compared
to any of the round numbers, implying apparent behavioral responses to the threshold.
2 Kleven and Waseem (2013) apply this convergence condition to estimate the counterfactual density for an individual
income tax notch in Pakistan. For individual tax rate kink points in Denmark, Chetty et al. (2011) determine the upper
limit visually, and then iteratively adjust the counterfactual density above the kink point such that it includes the excess
mass at the kink. This makes the estimated counterfactual density equal to the observed density. These procedures are
intuitively similar, but the convergence method of Kleven and Waseem (2013) typically provides a smaller estimate for
excess bunching. In addition, the convergence method provides a more justied approach to dene the upper limit of the
excluded region.
10
2000
4000
Frequency
6000
8000
Annual sales, all firms 2000−2011
2500
5000
7500
10000
12500
Sales
15000
17500
20000
Note: Bin width=100 euro
Figure 5: Annual sales of all rms, 2000-2011
In the following analysis, we restrict our sample by excluding those rms for which the VAT rules
or the VAT threshold are not binding. Thus all rms in sectors that produce nancial and insurance
activities, letting and operation of dwellings, education, human health and social work activities are not
included in our sample. In addition, we restrict the sample to include only rms with annual sales below
20,000 euros. Also, we exlude rms that are taxed by assessment of the Finnish Tax Administration,
as tax record information based on assessment does not provide evidence of behavioral choices of rms.
The most common reason for assessed taxation is that a rm has not declared its tax forms in time.
Table 1 oers the descriptive statistics of the data. The upper panel of the Table shows rm-level
statistics, and lower panel presents owner-level variables. From rm-level statistics we can see that most
of the rms in our sample of small businesses do not have any employees, and have low taxable prots,
expenses and assets.
The lower panel of the Table shows that sole proprietor is the most common organizational form
among small rms.
The average total income of the main owner (the sum of all wage and capital
income) is relatively low, less than 11,000 euros. However, it seems that many of the owners seem to
fulll our denition of a full-time entrepreneur, as over 60% of all main owners have more annual turnover
in their rm than they have total personal income.
11
Firm-level statistics
Sales
Expenses*
No. of empl.
Prots
Assets
Mean
8,942
3,633
.195
1,705
12,600
Median
7,962
2,071
0
758
1,492
SD
5,355
14,531
1.27
9,448
75,374
N
588,505
341,754
481,407
587,677
487,047
Min
1,500
17
0
-81,852
-141,825
Max
20,000
3,716,961
90
580,561
3,111,189
Owner-level statistics
Sole proprietors Corporations Partnerships Total inc. 'Full-time'
Mean
.688
.224
.088
11,821
.633
Median
1
0
0
4,390
1
SD
.463
.417
.283
18,005
.482
N
588,505
588,505
588,505
586,710
588,505
Min
0
0
0
0
0
Max
1
1
1
177,759
1
Sample: Sales between 1,500-20,000 euros per year. Pooled data from 2000-2011. *Information only from 2002 onwards.
Table 1: Descriptive statistics
5
Results
5.1 Baseline results
Figure 6 shows the sales distribution around the VAT threshold for all rms in our estimation sample
using pooled data from 2000-2011.
The gure plots the observed sales distribution (solid line) and
¿ in the range
counterfactual distribution (dashed line) relative to the threshold point in bins of 100
of +/- 7,000
region
¿ from the threshold.
[sL , sH ]
The threshold is marked with a dashed vertical line. The excluded
3
in the estimation of the counterfactual is marked with solid vertical lines.
The Figure
denotes the estimate for the excess mass at the threshold with bootstrapped standard errors, and the
estimate for the upper limit of the excluded region,
sH ,
which is determined by the iterative process
explained above. The upper limit also denotes the sales response of the marginal bunching rm,
∆s.
Excess bunching is measured by relating the number of rms in the observed sales distribution to the
counterfactual density within the region
[sL , 0].
3 The counterfactual density is estimated using a 7th-order polynomial function. Our results are not sensitive to the
choice of the order of the polynomial.
12
VAT threshold, all firms 2000−2011
2000
3000
Frequency
4000 5000
6000
7000
Excess bunching: 3.195 (.179)
Upper limit: 27 (2.44)
−70 −60 −50 −40 −30 −20 −10 0
10 20 30
Distance from the threshold
Observed
40
50
60
70
Counterfactual
Figure 6: Bunching at the VAT threshold, 2000-2011
Figure 6 illustrates that excess bunching is striking. A signicant proportion of small rms locate
themselves just below the VAT eligibility threshold. The estimate for excess bunching is notable and
strongly signicant statistically.
These imply that the VAT threshold clearly aects reported sales of
small businesses. We study how excess bunching evolves over time in Section 5.2.
In Table 2 we describe which types of rms bunch at the VAT threshold.
Column (1) of Table
2 shows the results from an OLS regression where we regress the dummy variable of locating in the
bunching region 7,600-8,500e with rm and owner-level characteristics. We also show the results for the
regressions on belonging to sales region below 6,600-7,500e in column (2) and above 8,600-9,500e the
bunching region in column (3). These estimations provide benchmark information on the characteristics
of small businesses close to the VAT threshold. Thus by comparing estimates in column (1) with columns
(2) and (3) illustrate which chracteristics correlate with bunching behavior.
13
(1)
Buncher: sales 7,600-8,500e
0.192***
0.093***
0.272***
(2)
Placebo 1: 6,600-7,500e
0.108***
0.058***
0.115***
(3)
Placebo 2: 8,600-9,500e
0.075***
0.045***
0.061***
-0.001
0.006***
-0.000
0.001
-0.003***
-0.012***
-0.003**
-0.006***
-0.001**
0.006***
0.008***
0.011***
0.017***
546,277
0.081
0.002
0.003**
0.005**
0.000
546,277
0.015
0.001
-0.003***
-0.001
-0.002**
546,277
0.006
Bunches t − 1
Bunches t − 2
(t-1)*(t-2)
Ref: corporation
Partnership
Sole proprietor
'Full-time'
Industry ref: Construction
Hotels and restaurants
Professional activities
Admin. activities
Arts
N
R2
Note: Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1. In column (1), buncher is 1 if sales is between 7,600 and 8,500
euros, 0 otherwise. In column (2), placebo 1 is 1 if sales is between 6,600 and 7,500 euros, 0 otherwise. In column (3), placebo 2 is 1 if
sales is between 8,600 and 9,500 euros, 0 otherwise. Estimation sample: Data from 2000-2011. Annual sales between 1,500 and 20,000
euros. Year dummies included.
Table 2: OLS regression results on locating below the VAT threshold, 2000-2011
First, we can see that past behavior signicantly explains bunching. Coecients for bunching in the
two previous periods (bunches
t−1
and bunches
t − 2)
and the interaction of the two
(t − 1 ∗ t − 2)
are positive and highly signicant statisticallt. Compared to regions below or above the threshold, it is
notably more likely to bunch again below the VAT threshold if the rm has previously located within
the bunching window. Thus it appears that bunching behavior is relatively permanent, which suggests
that the VAT threshold hinders the growth of small businesses. We study this issue in more detail in
Section 5.3.
The results indicate that sole proprietors bunch more actively than partnerships or corporations,
but the economic signicance of the organizational form seems to be small. Our measure for full-time
entrepreneur (turnover of the rm greater than personal taxable income) is not signicant, which suggests
that all types of entrepreneurs bunch at the threshold. However, on both sides of the bunching window,
it is more likely that owners of the rms have personal taxable income above the turnover of the rm.
Firms who bunch at the threshold do not come from any particular industries. However, bunching is
somewhat more likely among rms at the hotel and restaurant and arts industries.
5.2 Response to the notch vs. kink
Tax incentives at the VAT threshold changed in Finland in 2004. A VAT relief system was introduced in
2004, which implied a change from a VAT notch to a VAT kink, as explained in more detail in Section
2. This reform allows us to characterize the eect of the size of tax incentives at the threshold on rm
behavior. Intuitively, if the change in VAT liability and remitted VAT at the threshold matter, we should
see notably less rms bunching at VAT kink compared to VAT notch.
Figure 7 shows the sales distributions for all rms around the VAT notch (upper graph) and VAT kink
(lower graph) in 2000-2003 and 2004-2011, respectively. The Figure clearly shows that excess bunching
at the threshold is highly signicant and very similar in size both at the VAT notch and VAT kink. This
evidence implies that the size of tax incentives is not driving the extent bunching behavior.
Second, local elasticity estimate at the threshold is almost ve times smaller within the VAT notch
system compared to the VAT kink.
This is a reasonable result because the extent of the behavioral
response remained similar after the reform, but the relative change in the implied marginal VAT rate decreased notably. We have no reason to assume that the underlying tax responsiveness of small businesses
14
changed abruptly at the same time as the VAT relief was introduced. Therefore, the sudden increase
in sales elasticity strongly suggests that also other issues than a pure change in VAT rate explains why
rms actively avoid exceeding the VAT threshold.
500
1000
Frequency
1500
2000
2500
VAT notch, all firms 2000−2003
Excess bunching: 3.449 (.148), Elasticity: .1 (.012)
Upper limit: 26 (2.072)
−70 −60 −50 −40 −30 −20 −10 0
10 20
Distance from the notch
Observed
30
40
50
60
70
50
60
70
Counterfactual
1000
2000
Frequency
3000
4000
5000
VAT kink, all firms 2004−2011
Excess bunching: 3.029 (.169), Elasticity: .493 (.052)
Upper limit: 28 (2.328)
−70 −60 −50 −40 −30 −20 −10 0
10 20
Distance from the kink
Observed
30
40
Counterfactual
Figure 7: Bunching at the VAT notch and VAT kink
To further illustrate potential changes in rm behavior over time, Figure 8 presents excess bunching
estimates (upper graph) and local elasticity estimates (lower graph) in dierent years. The Figure shows
15
that excess bunching at the VAT threshold has remained approximately similar in 2000-2009. There is
no distinctive change in behavior in 2004 when the VAT kink was introduced. However, in 2010-2011,
excess bunching seem to have decreased slightly. This is potentially due to an increase in the salience of
the VAT relief system, which we will discuss in more detail below.
As a consequence of signicant and similar bunching responses under both schedules, the lower graph
in Figure 8 shows that local elasticity at the threshold jumps after the introduction of the VAT kink
system.
This indicates that the VAT rate elasticity at the threshold is unlikely to be an informative
measure of actual tax rate responsiveness of small businesses, as other issues besides the discontinuous
increase in VAT rate are likely to explain the bunching behavior.
Excess bunching and elasticity at the threshold over time
0
Excess bunching
1 2 3 4 5
Excess bunching
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2007
2008
2009
2010
2011
0
Elasticity
.2 .4 .6
.8
Elasticity
2000
2001
2002
2003
2004
2005
2006
Years
Estimate
CI
Figure 8: Excess bunching and elasticity at VAT threshold over time
Negligible changes in behavior after the change in the VAT rate at the threshold point out that other
issues than the VAT rate aect the behavior of small businesses. One plausible explanation is various
types of compliance costs. In addition to the tax penalty, rms face other costs if the VAT threshold is
exceeded. These include for example reporting and accounting costs and costs related to understanding
the details of VAT rules and regulations. In addition, more extensive reporting of sales and purchases
to the Tax Administration could make tax avoidance and evasion more dicult, as rms need to report
both sales and purchases to Tax Administration in more detail.
In general, it is challenging to analyze the role of compliance costs in observed behavior of rms.
These costs are typically unobserved by the researcher, and without experimental variation it is dicult
to identify any dierences in compliance costs between dierent rms using tractable assumptions. Nevertheless, the details of the Finnish VAT system allow us to characterize the eect of compliance costs
of VAT reporting among small businesses.
First, the Finnish system induces variation in the frequency of VAT reporting. Once a rm exceeds
the threshold, the required frequency of VAT reports depends on the amount of annual sales. From 2010
onwards, rms with sales between 8,500-25,000 euros report VAT annually, rms with 25,000-50,000 of
sales report quarterly, and rms with sales above 50,000 euros report monthly.
16
If costs related to each VAT report are important, we should nd rms bunching below the 25,000
and 50,000 euro thresholds.
However, Figure 9 does not support this hypothesis.
There is no excess
mass of rms below these sales thresholds. The spike exactly at 25,000 euros is likely a round-number
eect, which is also detectable at other convenient round numbers such as 30,000 and 40,000 euros.
Nevertheless, reporting frequency thresholds only describe reporting costs at the intensive margin when
the VAT eligibility threshold is already exceeded. Costs at the extensive margin of VAT reporting might
still be notable and explain the bunching behavior at the eligibility threshold of 8,500 euros. However,
Figure 9 highlights that pure costs of frequent VAT reports are not outstanding.
200
250
Frequency
300
350
400
450
Annual sales, all firms 2010−2011
20000
30000
40000
Sales
50000
60000
Note: Bin width=100 euro
Figure 9: Annual sales of rms and VAT reporting thresholds: 25,000e (quarterly) and 50,000e (annual
reporting)
Another important issue that might aect excess bunching after 2004 is the transparency of the VAT
relief scheme. First, all rms might not be aware of the existence of the VAT relief. Second, the relief
was not automatic and rms needed to declare the eligibility to the relief by ling a separate form.
Because of potential unawareness of the change in tax incentives at the threshold, it is possible that
excess bunching underestimates the eect of the change in tax incentives when comparing the VAT
notch and the VAT kink. Some fraction of rms might bunch below the threshold after 2004 because
they do not know or fully understand the VAT relief system. We do not observe whether rms below
the threshold are aware of the relief system or not. However, we do observe whether a rm has led the
separate rm to apply for the relief. Thus we can describe the general knowledge of the relief system by
studying how many rms above the threshold apply for the relief.
Figure 10 describes the take-up rates of the relief in 2004, 2007 and 2011. The vertical axis denotes
the share of rms that applied for the VAT relief. Dashed vertical line at 20,000 euros denote the end of
the relief region in 2004 and the 22,500 line in 2007 and 2011. .
Figure 10 oers the following insights: First, the approximated take-up rate is only between 30-60%
just above the threshold. This implies that a notable fraction of rms are not aware of the relief or do
not apply for it for one reason or another. Potential unawareness might increase bunching at the VAT
17
threshold if a notable fraction of rms below the threshold are unaware of the relief. However, the share
of rms that applied for the relief in Figure 10 probably underestimates the actual take-up rate. This is
because we cannot fully observe the actual eligibility for the relief among all rms, but we assume that
all rms not applying for the relief would be eligible
Second, the share of rms that applied for the relief decreases along with sales. This is reasonable as
the monetary benet from the relief also decreases at larger sales levels. Naturally, the take-up rate is
(close to) zero above the relief region.
Third, there is a signicant increase in the take-up rate in 2011. From 2010 onwards, rms could
apply for the relief with the same form they use to declare VAT liability. This seems to have increased
the share of rms that applied for the relief.
excess bunching estimate.
Importantly, the increase in take-up is reected in the
Figure 8 above shows that excess bunching moderately decreased in 2010-
2011 compared to previous years. This supports the view that the non-transparency of the relief system
aects observed rm behavior at the threshold, at least to some extent.
0
Share of firms
.2
.4
.6
Share of firms that applied VAT relief: 2004, 2007 and 2011
8500
10500
12500
14500
16500
Sales
2004
2011
18500
20500
22500
24500
2007
Bin width = 200 euros
Figure 10: Share of rms that applied for the VAT relief in 2004, 2007 and 2011
To summarize, excess bunching is signicant and very similar both within the VAT notch and the VAT
kink systems. This implies that compliance costs related to the extensive margin of VAT reporting are
important in explaining why rms actively stay below the VAT threshold. However, the negligible eect
of pure tax incentives is probably underestimated because of relatively low awareness and transparency
of the kink system. Nevertheless, it is unlikely that low salience fully explains the permanent bunching
eect over time. Observed excess bunching at the VAT kink would need to be approximately three times
smaller in order for the local VAT rate elasticities to be equal at the VAT notch and VAT kink.
5.3 Anatomy of the response and growth eects
Irrespective of whether rms stay below the VAT threshold because of tax incentives or compliance costs,
it is crucial to know how rms adjust their behavior. In terms of policy implications, it is relevant to
know whether rms respond by decreasing real economic activity, or by engaging in active tax avoidance
18
or evasion measures. Responses along all behavioral margins aect tax revenue. However, changes in
real economic activity can be considered more detrimental in terms of welfare, whereas changes through
tax avoidance and evasion might not aect the real allocation of resources with a similar magnitude (see
for example Slemrod 1992).
Furthermore, it could be easier for the government to aect evasion and
avoidance responses by more eectively monitoring small businesses. In contrast, it is more dicult to
inuence changes in the real economic activity of rms.
In order to illustrate the anatomy of the response, we study how the production factors reported
to the Tax Administration, such as equity and total expenses, evolve around the VAT threshold. Our
identication assumption is that in the absence of sales-based regulation, production factors should
develop smoothly as the sales of the rm increase. Therefore any discontinuous changes in production
factors exactly at the VAT threshold would indicate changes in rm behavior caused by this regulation
(see Almunia and Lopez-Rodriguez 2014). The existence of discontinuous jumps shed light on the nature
of the response.
Figure 11 shows the development of rm-level factors around the VAT threshold using pooled data
in 2000-2011. In the Figure, we plot a local polynomial function with standard errors using a bandwidth
of 100 euros to illustrate any changes in production factors at the threshold. Similarly as before, sales
are centered around the VAT threshold (+/- 5,000 euros).
The upper two graphs show that rm-level equity and wages paid increase smoothly as the sales of
the rm increase. There are no jumps in these variables at the VAT threshold. This implies that rms
around both sides of the threshold are equal in size, and suggests that rms do not locate themselves
below the threshold by active tax avoidance or evasion. For example, if larger rms would underreport
sales in order to bunch at the threshold, we would observe larger average equity levels just below the
threshold.
In contrast, the lower-left graph in Figure 11 shows that expenses jump at the threshold in a signicant
manner. This indicates that rms right below the VAT threshold use less expenses to achieve similar
level of sales.
Also, reporting more expenses above the threshold is more protable, as the rm can
deduct the VAT from purchases within the VAT system. However, this evidence does not point to active
avoidance or evasion decisions below the threshold. If rms would systematically underreport sales in
order to locate themselves below the threshold, we should nd that reported expenses are larger below
the threshold, not above it.
A jump in expenses suggests that rms below the VAT threshold have higher prot margins. This
notion is supported by the lower-right graph in Figure 11, which shows that rm prots decrease right
above the VAT threshold.
This is a reasonable result because rms below the threshold do not pay
VAT, and thus get more after-tax sales revenue with equal prices as rms just above the threshold. This
suggests that VAT threshold distorts competition between small businesses, as rms below the VAT
threshold are more protable.
Nevertheless, larger prot levels below the VAT threshold again imply that real economic decisions are
the probable source of responses. If rms would systematically underreport income, we should observe
smaller prots below the threshold. Firms that declare larger prots below the threshold also pay larger
income taxes, which is not in accordance with general avoidance or evasion behavior.
In summary, the evidence in Figure 11 suggests that avoidance and evasion responses do not explain
observed behavior.
However, as in other studies that utilize register-based data, we do not observe
intentional misreporting of business activity, such as operating partly in the black market. Therefore,
we cannot oer fully conclusive evidence of potential evasion eects of the VAT threshold.
19
Firm−level factors around the threshold
Local polynomial with 100 euro bandwidth
Wages
8.5
Log wages
7.27.47.67.8 8 8.2
Log equity
9
9.5
Equity
−5000
−2500
0
2500
5000
−5000
−2500
0
2500
5000
−2500
0
2500
Distance from the threshold
5000
Profits
Log profits
7 7.5 8 8.5
Log expenses
6.8
7.3
7.8
Expenses
−5000
−2500
0
2500
Distance from the threshold
5000
−5000
95% CI
Kernel function
Bandwidth: 100
Figure 11: Firm-level factors around the VAT threshold, 2000-2011
An additional avenue to avoid VAT would be to set up multiple rms and divide sales between them
such that none of the rms exceed the VAT threshold (see Onji 2009).
The left-hand side of Figure
12 shows the average number of rms per an individual owner (in sales bins of 100 euros around the
VAT threshold). The Figure shows that avoidance via multiple rms appears not to explain the observed
behavior, as there is no statistically signicant jump in the number of rms below the threshold. Overall,
the average number of rms per owner is very close to one. This is driven by the fact that an individual
cannot have multiple rms registered as sole proprietors in the Finnish business tax system. Most of small
businesses in Finland are registered as sole proprietors (69% of rms with sales between 1,500-20,000 are
registered as sole proprietors).
The right-hand side of Figure 12 presents the number of rms per owner when excluding sole proprietors. This graph indicates an increase in the number of rms per owner below the VAT threshold.
This implies that at least some owners utilize multiple rms as a mean to avoid VAT. Nevertheless, this
does not fully explain the overall bunching result. Figure 14 in the Appendix shows the sales distributions around the VAT threshold separately for dierent organizational forms.
The Figure shows that
excess bunching is evident among all types of businesses, and not driven solely by partnership rms or
corporations.
In terms of dynamic eciency and economic growth, it is essential to analyze whether the VAT
threshold hinders the growth of small businesses.
The threshold could signicantly decrease or even
eliminate potential growth rates if rms avoid exceeding the threshold for a prolonged period of time.
Figure 13 presents the growth rates of sales and rm-level production factors around the VAT threshold.
In the Figure, we calculate one-year logarithmic growth rates (t
− (t − 1)) of sales and various
t − 1. The upper-left
rm-level inputs conditional on locating in 100 euro sales bins in the base year
graph in the Figure shows that the growth rate of sales jumps right above the threshold. This implies
that rms permanently bunch below the threshold, which was also shown in Table 2 above. Also, compared to average growth of rms above, the VAT threshold appears to signicantly decrease the growth
of sales of small businesses.
20
Average number of firms per owner around the threshold
All firms
Partnerships and corporations
−5000
1.03
1.01
1.08
Number of firms
1.015
1.02
1.13
1.025
Local polynomial with 100 euro bandwidth
−2500
0
2500
Distance from the threshold
5000
95% CI
−5000
−2500
0
2500
Distance from the threshold
5000
Kernel function
Bandwidth: 100
Figure 12: Average number of rms per owner around the VAT threshold, 2000-2011
The three other graphs in the Figure show that there are also discontinuities of growth rates of rmlevel production factors around the threshold. It seems, for example, that the growth rates of expenses
(upper-right graph) and wages (lower-right graph) are lower just below the threshold that above it.
However, these results are less apparent than that observed in the sales growth.
Nevertheless, this
further suggest that the threshold creates obstacles for rms to grow, and that the behavior is driven by
the changes in real economic activity of rms.
21
Growth of firm−level productions factors around the threshold
Local polynomial with 100 euro bandwidth
expenses
−.05 0
.05
.1
−.02 0 .02.04.06.08
sales
−5000
−2500
0
2500
5000
−5000
0
2500
5000
−2500
0
2500
Distance from the threshold
5000
wages
0 .02.04.06.08.1
−.1 0 .1 .2 .3
equity
−2500
−5000
−2500
0
2500
Distance from the threshold
5000
95% CI
−5000
Kernel function
Bandwidth: 100 euros
Figure 13: The growth rates of rms around the VAT threshold, 2000-2011
6
Conclusions
In this paper we study the eects of the VAT threshold on the behavior of small businesses. In Finland,
rms with annual sales below 8,500 euros are not liable to register and pay VAT. We use detailed tax
register data and the bunching method to provide clear and intuitive evidence on the eects of the
threshold.
We nd that the VAT threshold has notable eects among small businesses.
Bunching below the
threshold is highly signicant, which implies that rms actively avoid exceeding the threshold.
This
implies notable eciency implications.
We nd that changing the tax system from a VAT notch to a VAT kink does not signicantly decrease
the eect. This suggests that compliance costs largely explain observed responses. We nd no clear traces
of tax avoidance or evasion, which suggests that rms respond by reducing output. Finally, we nd that
bunching behavior is relatively permanent, which implies that the threshold decreases the growth of
small businesses.
22
References
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23
Appendix
Excess bunching at the VAT threshold by organizational form, 2000−2011
Corporations
Excess bunching: 2.054 (.222)
Upper limit: 29 (2.367)
Frequency
2000 4000 6000
500 1000 1500
All firms
Excess bunching: 3.195 (.179)
Upper limit: 27 (2.44)
−40
−20
0
20
40
60
−60
−60
−40
−20
0
20
40
Sole proprietors
Excess bunching: 3.653 (.138)
Upper limit: 26 (1.766)
1000 3000 5000
Partnerships
Excess bunching: 2.303 (.243)
Upper limit: 34 (2.822)
Frequency
200 400 600
−60
−40 −20
0
20
40
Distance from the threshold
60
−60
Observed
−40 −20
0
20
40
Distance from the threshold
60
60
Counterfactual
Bin width = 100 euros
Figure 14: Bunching at the VAT threshold for dierent organizational forms, 2000-2011
24