How Responsive are Firms to the
Corporate Wealth Tax?
Camilo Gómez
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Universidad de los Andes | Vigilada Mineducación
How Responsive Are Firms to the Corporate
Wealth Tax?
a
Camilo G´
omez
bAbstract
The corporate wealth tax is commonly associated with a non-optimal policy for fiscal
revenue and efficiency. However, there is no empirical evidence regarding the behavioral
response of firms to this tax. Taking advantage of the non-linearities introduced by the
tax design in Colombia, this paper estimates the elasticity of corporate wealth with
respect to the statutory tax rate and investigates the impact of the tax on reported
assets, profits, and liabilities. Results reveal that, in years 2006 and 2010, we observe
between 23.8% and 35.7% more firms at the wealth cutoffs where the tax rate changes.
This implies estimated elasticities of 0.250 and 0.447 for firms with wealth around 3
billion pesos. Difference-in-differences analysis suggests that the reduction in reported
wealth relates mostly to declines in assets and pre-tax profits, while no effects on
lia-bilities are found. Absent fiscal externalities, the estimated elasticities are associated
with a revenue loss and marginal deadweight loss of around 1% of fiscal revenue on the
evaluated taxpayer firms. Once the negative impact on the corporate income tax is
considered, these figures can be as high as 3.8%.
JEL Classification: H25, H26, H32, D22.
keywords: Corporate wealth tax; wealth tax base elasticity; Colombia.
aAn early draft of this document was presented in Spanish as a thesis for the Master in Economics at
Universidad de los Andes. I am grateful to my advisor, Ligia Melo, for her guidance during this research
process. I also thank Paula Jaramillo, Mar´ıa Jos´e Gonz´alez, Leopoldo Fergusson, Ignacio Lozano, and
seminar participants at IFABS 2019 Conference for their comments and suggestions. All opinions, errors, and omissions are my own and do not represent the official positions of the institutions where I work.
bBanco de la Rep´ublica and Universidad de los Andes, Bogot´a, Colombia. E-mail:
¿Qu´
e tanto responden las empresas al
impuesto a la riqueza?
a
Camilo G´
omez
bResumen
La evidencia emp´ırica sobre la respuesta de reporte al impuesto a la riqueza corporativa
es inexistente. Sin embargo, este impuesto com´unmente es asociado con un tributo no
´
optimo en t´erminos de recaudo y eficiencia. Este art´ıculo explota las variaciones ex´
oge-nas inducidas por los umbrales de riqueza en los que cambia la tasa del impuesto en
Colombia para estimar la elasticidad de la riqueza corporativa con respecto a la tasa
estatutaria del tributo y para identificar el efecto del impuesto sobre los activos, las
utilidades y los pasivos. De acuerdo con los resultados, para los periodos 2006 y 2010
observamos, en los umbrales del tributo, entre 23.8 % y 35.7 % m´as firmas que las que
habr´ıa en ausencia del impuesto. Esto implica elasticidades estimadas de 0.250 y 0.447
para las empresas con riqueza cercana a los 3,000 millones de pesos. Las estimaciones
de diferencias en diferencias indican que el subreporte de riqueza se relaciona
principal-mente con reducciones en activos y utilidades, mientras que no se encuentran efectos
en los pasivos. Ausentes externalidades fiscales, se encuentran p´erdidas de recaudo y
eficiencia de aproximadamente 1 % del ingreso fiscal para las firmas evaluadas. Una vez
se tiene en cuenta el efecto negativo sobre el impuesto a la renta, estos impactos pueden
ser de hasta 3.8 %.
Clasificaci´on JEL: H25, H26, H32, D22.
Palabras claves: Impuesto a la riqueza corporativa; elasticidad de la base gravable; Colombia.
aUna primera versi´on de este documento en espa˜nol fue presentada como tesis para optar al grado de
Maestr´ıa en Econom´ıa de la Universidad de los Andes. Agradezco a mi asesora Ligia Melo por su gu´ıa en
la realizaci´on de esta investigaci´on. Agradezco tambi´en a Paula Jaramillo, Mar´ıa Jos´e Gonz´alez, Leopoldo
Fergusson, Ignacio Lozano y los participantes de la conferencia IFABS 2019 por sus comentarios y observacio-nes. Las opiniones, errores y omisiones son responsabilidad exclusiva del autor y no representan las opiniones oficiales de las instituciones a las que pertenece.
bBanco de la Rep´ublica y Universidad de los Andes, Bogot´a, Colombia. E-mail:
1
Introduction
Taxation of corporate wealth is commonly regarded as a non-optimal policy in terms of fiscal
revenue and efficiency (Brown, 1991; OECD, 2018). The arguments against this policy mainly
rest on the assumption that it is more difficult for the tax authority to monitor the valuation
that taxpayers make of their stocks, since this would increase the evasion opportunities faced
by firms and would end in a high distortion of their decisions. Furthermore, even with perfect
monitoring of wealth, the literature points out that the taxation of firms’ wealth may have adverse effects on capital accumulation and economic activity.
In contrast to the previous critiques, we know nothing about the responsiveness of firms
to the corporate wealth tax.1 To fill this gap in the literature, this paper aims to investigate
the reporting response of companies to this tax. More specifically, this article estimates the
elasticity of firms’ wealth with respect to the statutory tax rate and investigates which kinds
of behavioral responses are related to the reduction of wealth triggered by the tax.
Estimating the elasticity of the taxable base (ETB, hereafter) is useful because, absent
fiscal externalities, this parameter is asufficient statistic that allows us to assess the effects of
taxes on fiscal funds and efficiency (Saez et al., 2012). First, the ETB quantifies the impact of agents’ reporting responses on fiscal balance. Second, since adjustments to taxes (e.g.,
countable alterations, changes in financial structure, purchase or sale of assets, among others)
are costly for taxpayers, the ETB measures the influence of the tax burden on economic
efficiency. Indeed, the higher the elasticity, the higher the distortions on taxpayers decisions
and the marginal deadweight loss associated with the tax.
All the power of the ETB approach, however, depends crucially on the fact that it is a
partial equilibrium analysis. Thus, it does not consider the possible impacts of taxes over
other economic agents. For example, when a tribute on corporations is evaluated, the basic
ETB analysis does not take into account the effects on households’ decisions. Similarly, in the presence of fiscal externalities like base shifting, the ETB framework can overestimate or
underestimate the actual influence on fiscal revenue and efficiency (Chetty, 2009). This paper
investigates the following questions for assessing to what extent is this kind of externalities
relevant: Is the reduction of wealth related to increases in liabilities or decreases in assets?
Or do firms report lower pre-tax profits because of the taxation of wealth?
The empirical analysis is carried out at the firm level, using the financial statements
reported by companies to the Colombian Superintendency of Corporations in the period 2003–
2011. For the identification of behavioral responses to the wealth tax, we employ as a source
1As far as we know, there are no published empirical articles that quantify the behavioral response of firms
of exogenous variation the tax law changes introduced by the Colombian government in the
period of study. During these years, the government implemented four major modifications
(Tax Laws of 2003, 2006, and 2009, and Decree 2825 of 2010) that introduced the tax and modified the intervals of wealth and the statutory rates associated with each interval.
Therefore, the Colombian institutional context is an ideal quasi-experimental scenario for
identifying behavioral responses to the corporate wealth tax.
The main advantage of studying the Colombian setting is the implementation of wealth
cutoffs where taxpayers face discrete tax rate jumps, i.e., notches. For instance, the 2006
tax reform establishes that firms with wealth below 3 billion pesos are subject to a tax
rate of 0%, while those with wealth above this value are subject to a rate equals 4.5%.
These notches in the tax liabilities of firms generate incentives for reducing the reported
wealth to the threshold where the tax rate changes, allowing us to uncover the elasticity by using the bunching methodologies introduced by Saez (2010) and extended by Chetty et al.
(2011), and Kleven and Wassen (2013). These methods consist of comparing the wealth
distribution near the cutoff with the counterfactual distribution without cutoff. Besides, the
Colombian institutional context enables us to investigate the nature of the reporting response
by conducting a difference-in-differences analysis akin to Seim (2017), which compares the
evolution of assets, liabilities, and profits of firms just above and below the cutoff.
The bunching method presents advantages with respect to the panel data methods
em-ployed in the ETB literature, as it is not necessary to deal with the endogeneity issues deriving
from the correlation between the tax rate measure and the changes in the distribution of cor-porate wealth.2 In turn, the exogeneity of the wealth cutoffs mandated by the Colombian
government offers a credible difference-in-differences design to uncover the anatomy of the
behavioral response of firms.
Results reveal that for institutional contexts with moderate tax rate changes and where
the policy of wealth taxation is a transitory measure, as it is the case for the 2003 reform,
firms do not bunch in the distribution of wealth. In contrast, the estimates concerning the
tax environments of 2006 and 2010 indicate that companies react to the corporate wealth
tax in scenarios with higher rates and permanent tax. According to our findings, in 2006
and 2010 we observe 35.7% and 23.8% more firms at the respective 3 billion pesos cutoffs of
wealth where the tax rate changes.
The bunching found is associated with elasticities between 0.250 and 0.447, indicating
a negative and inelastic effect on corporate wealth when the statutory tax rate increases.
Nevertheless, unlike the bunching estimates, the identified elasticities are not statistically
different from zero. This weak statistical precision might obey to the low statistical power
of the elasticity estimations, which in turn may be rooted in the number of observations in
the sample and the noise that it generates on the observed distribution.
The difference-in-differences analysis shows that the reduction in wealth found manifests as declines in assets and profits. Regarding liabilities, we find no robust and statistically
significant effect.
Assuming that fiscal externalities are absent and considering the tax rate and the elasticity
estimate of each reform, we obtain lower bounds for the revenue decline and the marginal
deadweight loss of around 1% of fiscal income on the assessed firms.3 Once the revenue
impact linked to the reduction in profits is considered, these figures can be as high as 3.8%.
One could be tempted to interpret our findings as if the magnitude of firms’ behavioral
responses and the inefficiencies associated with the taxation of corporate wealth were low.
A relevant issue limiting our analysis, however, forces us to be cautious when interpreting it. The method used in estimations allows us to uncover the responses of firms with wealth
neighboring the cutoffs of the tax. Therefore, as long as there is heterogeneity in elasticities,
we must read our findings as local effects on firms with these levels of wealth. Section 4
characterizes the differences between companies with wealth around the cutoffs evaluated in
this paper and the rest of companies. This analysis concludes that our findings correspond
to big-size firms measured in wealth, assets, and income.
The paper at hand contributes to the previous literature by informing policy about the
responsiveness of firms to the taxation of wealth. Despite there is a growing body of literature
about the elasticity of the personal wealth tax (Br¨ulhart et al., 2016; Seim, 2017; Jakobsen et al., 2018; Londo˜no and ´Avila, 2020), no attention has been paid to the corporate wealth
tax.4 Thus, this study provides the first impact assessment of wealth taxation when it is
implemented on the stocks that people own legally in the form of companies. The above
speaks to the renewed public and scholar debate about the possibility of wealth taxation as a
measure for reducing wealth inequality (Saez and Zucman, 2019). Furthermore, the present
research is of particular relevance for developing economies, given that their fiscal balance
heavily depends on the earnings arising from taxes on corporations (Gordon and Li, 2009).
This paper is also connected to the recent interest in identifying the ETB of corporate
taxes. Although several studies investigate the impact of corporate taxation on other
vari-3As we mention in Section 7, these figures do not correspond to the effect on the firms that bunch at the
cutoff. Therefore, the calculated revenue and efficiency effects are for corporations that (i) have a wealth level near to the 3 billion pesos cutoff; and (ii) do not bunch, i.e., firms that contribute to the revenue obtained from the corporate wealth tax.
4A possible explanation for this gap in the literature could be the tendency toward its elimination that the
ables,5 the abundance of articles about the ETB of personal taxes6 contrasts with the scant
evidence on the ETB of corporate taxes. Nevertheless, to estimate the elasticities related to
the taxation of companies is crucial, given the importance of firms on economic activity and fiscal balance.
With estimates varying in the range between -0.5 and 1 (Gruber and Rauh, 2007; Dwenger
and Steiner, 2012; Devereux et al., 2014; Melo-Becerra et al., 2018), the studies evaluating
the corporate income tax confirm that the elasticity depends on the institutional context and
firms’ characteristics. Our contrasting findings for the 2003 reform and the tax environments
of 2006 and 2010 highlight that the reaction of companies to the taxation of wealth also
depends on the institutional setting. Besides, our estimates allow comparing the magnitude
of the behavioral response of firms to the corporate wealth tax with the one associated with
the taxation of corporate income. The last part of this paper provides an attempt in this direction.
The rest of this paper proceeds as follows. Section 2 summarizes the main characteristics
of the tax system in Colombia, making special emphasis on the wealth tax design. Section 3
introduces the conceptual framework and the elasticity identification strategy deriving from
it. Section 4 presents the data. Section 5 shows the main findings of elasticity and bunching.
Section 6 describes and conducts the difference-in-differences analysis used to inquire about
the anatomy of the behavioral response of firms. Based on the main results, Section 7
quantifies the effects of the corporate wealth tax on fiscal revenue and efficiency. Section 8
discusses the main findings and concludes.
2
Colombian Institutional Context
Until recently, Colombia was one of the few countries that still employed the taxation of
corporate wealth as a source of fiscal revenue. Indeed, in 1990 ten OECD country members
collected resources from the corporate wealth tax, whereas in 2016 the quantity reduced to
six.7 In addition, the Colombian institutional context characterizes by its high frequency of
tax law modifications. Since the beginning of the previous decade, the frequency of tributary
reforms has been approximately one reform every three years. Furthermore, these reforms have been distinguished by their diversity since they have modified the taxable bases’
defi-nitions and have introduced and eliminated different taxes, benefits, and deductions.
Table 1 summarizes the main changes in the corporate wealth tax implemented by the
5See Hanlon and Heitzman (2010) for a literature review.
6Following the seminal contributions by Feldstein (1995, 1999), an extensive literature that estimates the
elasticity of the personal taxable income has been developed. See Saez et al. (2012) for a review.
Colombian government during the whole period 2003–2011. The Tax Law 863/2003
intro-duces the wealth tax for companies and individuals that contribute to the income tax. The
tribute is named impuesto al patrimonio and, in its origins, was established as a transitory measure. The initial objective of the policy was to obtain resources for fighting the guerrilla
groups of the country.
Table 1: Main Changes in the Wealth Tax Design, 2003–2011
Tax Reform Year Nominal Cutoff Real Cutoff Tax Rate
(2004 Prices)
2003 Reform 2004 3,000,000 3,000,000 0.3%
(Tax Law 863) 2005 3,106,317 3,000,000 0.3%
2006 3,239,774 3,000,000 0.3%
2006 Reform 2007 3,000,000 2,632,056 4.5%
(Tax Law 1111) 2008
2009 2010
2009 Reform 2011 1,000,000 744,020 1.0%
(Tax Law 1370) 2011 2,000,000 1,488,040 1.4%
and Decree 2011 3,000,000 2,232,061 2.9%
2825/2010
Notes: Cutoff values in thousands pesos. Source: Author’s elaboration based on the Tax Laws.
The 2003 reform establishes the wealth tax for 2003–2006 on the taxpayers that, on the
1st of January of each year, have a wealth above 3 billion pesos at 2004 prices (USD 1.091 million). As a result, the cutoff from which tax filers have to contribute to the wealth tax
rises in nominal terms through years. The statutory tax rate implemented by the 2003 reform
is equal to 0.3% in each tax year.
Once the state of being in force finished, the 2006 reform (Tax Law 1111) reintroduces
the wealth tax for the period 2007–2010 but adding some modifications. The new legislation
reduces in real terms the cutoff and increases the statutory tax rate. The tax now is charged
on the taxpayers that own on the 1st of January 2007 a wealth above 3 billion pesos, which is
equivalent to 2.632 billion pesos at 2004 prices (USD 0.957 million). Besides, the government
raises the statutory tax rate to 1.2%. One interesting peculiarity of this scheme is that the tax burden is defined on the base reported in 2007. Hence, the companies that filed a wealth
greater than 3 billion pesos had to pay the tax during 2008–2010 even if, in this period, they
reported a lower value. Therefore, taking into account the effect of inflation, the real tax
rate established for 2007 is 4.5%.8
8 The real tax rate for 2007 is:
1.2·
1 + 1
CP I2008
2007
+ 1
CP I2009
2007
+ 1
CP I2010
2007
,
where CP I2007j is the Consumer Price Index for the year j = 2008,2009,2010, and with 2007 as the base
The Tax Law 1370/2009 and the Presidential Decree 4825/2010 extend further the wealth
tax until 2011, modify the statutory tax rate, and create new cutoffs. In the first place, the
2009 reform mandated a statutory tax rate of 2.4% for wealth above 3 billion pesos (2.232 2004 billion pesos or USD 0.812 million) and of 4.8% for wealth greater than 5 billion pesos
(3.720 2004 billion pesos or USD 1.353 million).
The next year, arguing the need for funds to finance the expenses caused by the drastic
weather conditions, the president established a State of Emergency through Decree 4825,
which appends two new wealth thresholds and implements a surcharge of 25% to the tax rate
associated with the 3 billion pesos cutoff. The new cutoffs are 1 billion pesos with a tariff of
1.0% and 2 billion pesos with a tax rate of 1.4%. In this setting, the tax is defined on the 1st
of January 2011 and is paid in eight equal fees over years 2011, 2012, 2013, and 2014. Then,
the real tax rate faced by firms with wealth between 3 and 5 billion pesos is 2.9%.9
Lastly, the 2014 reform (Tax Law 1739) changes the name of the tax to impuesto a la
riqueza and establishes it until 2018. the new Law changes the tax base definition and the
tax liability design. With this reform, the government defines the tax base as assets minus
debts and deploys a system of marginal tax rates.
During the period of analysis, the wealth tax was designed as a progressive tax system
in which each wealth interval has a different average statutory tax rate. For instance, in
2004–2006, wealth less than or equal to 3 billion pesos is subject to a tax rate of 0%, while
wealth above this value is subject to a tax rate of 0.3%. The wealth cutoffs generate
discon-tinuities,notches, in the budget constraints of firms. The above, together with the variations introduced by the Laws, allows us to uncover behavioral responses to the tax.
Before 2014, the wealth tax is charged on the net worth of taxpayers, i.e., the fiscal value
of assets minus liabilities. The Colombian tax system also provides some deductions like the
value of shareholdings on national corporations. In general, wealth decomposes into financial
wealth (e.g., banking accounts, shares, securities) and non-financial wealth (e.g., vehicles,
real estate, inventories). The former type of wealth is subject to third-party registration. In
contrast, since the Colombian tax authority does not verify it systematically, the reporting
of the latter kind of wealth presents a more discretionary choice of the taxpayer (Londo˜no
and ´Avila, 2020).
As usual in developing countries (Gordon and Li, 2009), in Colombia the main components of fiscal revenue are reported by firms. Indeed, the major sources of fiscal earnings for the
Colombian Central Government are the value-added tax (VAT) and the corporate income tax.
In 2016, the revenue obtained from the corporate income tax was of about 6% of GDP, while
liability compared to a tax scheme in which the tax burden cannot be deferred over time.
the VAT revenue was close to 4% of GDP.10 The founds obtained from the corporate wealth
tax varies between 0.3% and 0.7% of GDP, depending on the year. The higher proportions
of revenue are observed for the years after the 2006 reform, which increased the number of taxpayers and the statutory tax rate.
3
Conceptual Framework and Elasticity Identification
Strategy
This section develops a tax avoidance model of the kind introduced by Usher (1986).11 We
extend the model to the wealth reporting decision of firms without covering its general
equilibrium effects. In our conceptual framework, the firm aims at maximizing the owners’ after-tax wealth by concealing a part to the tax authority. The amount concealed generates
costs to the firm. We firstly analyze the firm’s decision in a linear tax system where the
government charges a fixed statutory tax rate. Second, following Kleven and Wassen (2013),
we show how the introduction of a notch in the tax schedule, as in Colombia, allows us to
uncover the elasticity of corporate wealth.
Linear Tax System
Consider a firm with wealthW in absence of taxes that must reportWRto the tax authority,
where 0≤WR≤W. The government charges a tax liabilityT(WR) to the firm. We suppose
that T is a non-negative function. In our setting, the firm seeks to diminish the tax burden
by reportingWR < W. ChoosingWR< W makes the firm to incur a concealment cost equals
g(W−WR). This function represents the avoidance technology of the economy. For instance,
it measures the effort made by the accounting unit to reduce the company book value or the
substitution from real wealth toward another factor of production.12 We suppose that g is
continuous, non-negative, increasing, and strictly convex. The increasing assumption implies
that the avoidance cost is higher for higher levels of evasion. As well, from the strict convexity of g it follows that, marginally, the firm has to devote more resources to conceal one unit of
wealth. We also suppose thatg(0) = 0, that is, no avoiding does not generate costs. Lastly, g
represents a certain cost of concealing an amountW−WR. Hence, we are not considering an
uncertain decision in which there is a positive probability of being caught by the government.
10Ministerio de Hacienda y Cr´edito P´ublico and Direcci´on de Impuestos y Aduanas Nacionales.
11See Slemrod (2001) and Chetty (2009) for different applications of this type of model.
12Therefore, we are not distinguishing between real and evasion responses to taxes. Thegfunction summarizes
The firm’s problem is to maximize the owners’ after-tax wealthWN and reads as follows:
max
WR∈[0,W]
WN =W −T(WR)−g(W −WR). (1)
Let us study the case of a linear tax design with a statutory tax rateτ. In this scenario,
T(WR) = τ ·WR. Therefore, from the first-order condition, it follows that in the interior
solution τ =g0(W −WR). According to this, the firm reduces the reported wealth until the
marginal benefit τ and the marginal cost g0(·) of hiding one unit of wealth equalize. By the strict convexity of g, the disclosed wealth is decreasing in τ.
The elasticity e of corporate wealth with respect to the net-of-tax rate (1−τ) that we
aim to identify is defined as:
e= ∂WR
∂(1−τ) ·
(1−τ)
WR
. (2)
This parameter indicates the percentage change in wealth when facing a percentage increase in the net-of-tax rate. Since WRis decreasing in τ,e >0. As a result, the agent reports more
wealth when the after-tax value (1−τ) increases. In other words, since firms modify their
behavior due to taxation, they depress the reported wealth, and the degree of the response
is given by the elasticity. As we shall detail in Section 7, under the assumption of no fiscal
externalities, e is a sufficient statistic that summarizes the host of behavioral responses of
firms to the corporate wealth tax (Saez et al., 2012).
If there are smooth distribution and density functions F(W) and f(W) of the wealth
W that we would observe without taxes, then the reported wealth has smooth distribution
and density functions H0(WR) and h0(WR) as well.13 With this in mind, let us study how
a non-linear tax scheme generates incentives for bunching at the cutoff where the tax rate
changes and how this allows us to identify the elasticity.
Tax Scheme with Notch and Identifying Strategy
The Colombian legislation implemented a tax schedule with notches. In this design, wealth
above the notch point WR∗ is charged with a statutory tax rate τ + ∆τ.14 Thus,
T(WR) = τ·WR+ ∆τ·WR×1[WR> WR∗], (3)
where1[·] is the indicator function. For example, with the 2010 criteria,WR∗ = 3 billion pesos,
τ = 0.014, and ∆τ = 0.015. Notice that the budget constraintT experiences a discrete jump
13See Appendix A.
14When there is more than one threshold, they can be treated in isolation as long as they are not too close
in the average tax rate at the notch point WR∗ (higher statutory tax rate τ+ ∆τ), and that in this value T has a notch.
The notch in the budget constraints induces firms to fileWR∗ because the non-linearity in the tax liability generates incentives to pay fewer taxes by recording the notch point. Figure
1 illustrates this. LetWH be the wealth of the marginal bunching firm that in the linear tax
system disclosesWR∗+∆WR∗ and, given the notch, is indifferent between reporting the interior solution to the notch WI
R > W
∗
R and W
∗
R. Analogously, let us call L the firm with wealth
WL< WH that in both tax designs locates atWR∗. As revealed by Figure 1, those companies
that before the notch reported WR ∈ (WR∗,∆W
∗
R) can increase the after-tax wealth WN by
reporting WR∗ instead of choosing the interior solution to the notch.15
Figure 1: Behavioral Response of Firms to the Notch
H H’
L
Source: Author’s elaboration.
Therefore, there will be bunching at the notch point by firms that, before the notch introduction, had reported wealth in (WR∗, WR∗ + ∆WR∗). Hence, we will observe a peak in the wealth distribution at WR∗ and a hole above it. Depending on the heterogeneity in the avoidance costs of firms and the frictions they face, the manifested wealth distribution varies
according to the two following cases.
(i) Homogeneity in elasticities and absence of frictions. In this case, the avoidance
tech-nology is the same for all firms, and there are no frictions and optimization errors.
Thus, e is homogeneous, and all companies that reported WR ∈ (WR∗, WR∗ + ∆WR∗) in
the linear tax design locate atWR∗. Figure 3, Panel (a), depicts the wealth density that
we would observe in this scenario (blue line) and the density that there would be in a
linear tax design (black line). In this case, the excess bunching mass B is equal to:
B =
Z WR∗+∆WR∗
W∗
R
h0(WR)dWR≈h0(WR∗)·∆W
∗
R,
where the approximation assumes that h0 is constant close to WR∗.
Figure 2: Wealth Density with Notch
W∗
R W
∗
R+ ∆W
∗
R
WR
Density
Beforenotchh0(WR)
Observed withnotch
(a) Case (i) Homogeneity in elasticities and absence of
frictions
WR∗ W∗
R+ ∆WR∗(¯e)
Frictions are too high
eis too low
WR
Density
Beforenotchh0(WR)
Observed withnotch
(b) Case (ii) Heterogeneity in elasticities and frictions
Source: Author’s elaboration.
(ii) Heterogeneity in elasticities and frictions. Figure 3, Panel (b), displays the distribution
that we would observe in this scenario. Frictions trigger two effects on the observed
excess mass is diffuse and appears to the left of the cutoff WR∗. Second, forWR> WR∗,
a share of firms does not target WR∗ due to high frictions with high costs (gray area).
The latter is strengthened by the heterogeneity in elasticities. With elasticities varying
in the interval (0,¯e], the response of the marginal bunching firm which is indifferent
between choosing WR∗ andWR∗+ ∆WR∗(e) depends on the elasticity. Supposing that the greater the elasticity, the higher the reaction to the notch ∆WR∗(e), for each level of wealth WR∗ + ∆WR∗, one fraction of agents does not bunch at the notch point WR∗ due to their elasticities are too low (dark-gray area). Thus, the convergence point of the
before-notch density and the observed distribution with notch isWR∗+ ∆WR(¯e) (Kleven
and Wassen, 2013).
Definingα(e, WR) as the fraction of firms that, given an elasticity and a level of reported
wealth, do not locate at WR∗ because frictions are too high, and defining ¯h0(WR, e) as
the joint density distribution of WR and e, B is:
B = Z
e
Z WR∗+∆WR∗(e)
WR∗
(1−α(WR, e))·h¯0(WR, e)dWRde ≈(1−α)·h0(WR∗)·Ee[∆WR(e)],
where the approximation supposes that ¯h0(WR, e) is locally constant inWR∗ andα(WR, e)
is constant and equal to α in WR ∈(WR∗, W
∗
R+ ∆W
∗
R(e)) for all e. Notice that in this
case the average wealth response Ee[∆WR∗(e)] is attenuated by frictions.
Since empirically the relevant case is (ii), hereafter we suppose that ∆WR∗(e) depends on the elasticity e. The notch tax design defines an implicit marginal tax rate τ∗, which
relates the change in T to the change in the reported wealth at the notch point WR∗: τ∗ =
T(WR∗+∆WR∗(e))−T(WR∗)
∆WR∗ =τ+∆τ·
WR∗+∆WR∗(e)
∆WR∗(e) .The reduced-form elasticityeRproposed by Kleven and Wassen (2013) takes the response ∆WR∗(e) as if it were generated by the implicit marginal tax rate τ∗. Defining ∆τ∗ =τ∗−τ, eR is:
eR =
∆WR∗(e)
W∗
R
∆τ∗
1−τ∗
. (4)
This approximation to the elasticity presents advantages since it does not assume any
particular functional form for the avoidance technology g. Even, g can be firm-specific.
However, as Kleven and Wassen (2013) argue, the non-parametric elasticity given by (4) can
overestimate the real response of firms to the rate τ∗, as there could be feasible solutions
WR > WR∗ preferred over W
∗
(2018) propose the following formula for the elasticity
eR ≈
1 2 ·
∆W∗
R(e)
WR∗
2
∆τ
1−τ
, (5)
which adjusts τ∗ to reduce the bias generated in equation (4).16
For the calculation ofeR, eitherτ,∆τ and WR∗ are known parameters, given by each tax
regime. On the other hand, the estimate of the response to the notchabsent frictions ∆WR∗(e) is conducted following the convergence method proposed by Kleven and Wassen (2013). This method supposes that the quantity of firms locating in the interval (WR∗, WR∗ + ∆WR∗(¯e)) is given by those companies that face too high friction costs for bunching. Given this, this
method finds ∆WR∗(¯e) as the point where the excess bunching mass B equals the missing mass to the right of the cutoffWR∗. However, as argued in Case (ii), if there is heterogeneity in elasticities, then the value ∆WR∗(¯e) found with this procedure corresponds to the response of the firms that modify their behavior the most when facing a tax change. Then, our elasticity
estimates are upper bounds of the average elasticity.
Figure 3: Estimation Process
WR∗
WL
R WRU
WR
F requency
Counterfactual Observed
Source: Author’s elaboration.
The basic insight of the convergence method is to compare the wealth distribution
with-out notch with the one that we observe in the presence of notch. Thus, we estimate a
counterfactual distribution based on the interval of wealth not affected by the cutoff. Figure
3 illustrates this process.
First, we group firms in wealth bins j and define the number of observations in each bin
as cj. Afterward, we estimate regression
cj = p
X
k=0
βk·(WRj)k+ WU
R X
i=WL R
γi×1[WRj =i] +εj, (6)
where WRj is the wealth level of bin j, p is the degree of the polynomial, and εj is an error
term. From this expression, WRL and WRU define the excluded interval of wealth affected by the notch, as Figure 3 shows. Second, we calculate the counterfactual distribution ˆc as the predicted value of regression (6), eliminating the notch effects: ˆcj =Ppk=0βˆk·(WRj)k.Third,
we compute the estimates of the excess bunching mass of firms ˆB and the missing mass ˆM.
The former equals the difference between the observed and the counterfactual distribution
in the domain [WL R, W
∗
R], ˆB =
PWR∗
j=WL R
(cj −cˆj). Similarly, the estimate of the missing mass
ˆ
M is P
W∗
R<j≤WRU(ˆcj −cj).
The valueWRLis chosen visually based on the wealth level from which firms start to bunch in the distribution of wealth. On the other hand WRU is estimated in such a way that ˆM = ˆB. Specifically, we initiate with a conjecture of WU
R ≈ W
∗
R and calculate ˆB and ˆM. Based on
the comparison between ˆM and ˆB, we increase (or decrease) WU
R until ˆM ≈Bˆ.
The last procedure provides an estimate of the marginal bunching firm’s wealth WU R =
WR∗ + ∆WR∗(¯e) that allows us to compute the elasticity by using equation (5). Besides, we calculate the bunching degree b as the ratio between ˆB and the sum over [WL
R, W
∗
R] of the
counterfactual ˆcj, which is a relative measure of the number of firms that are gathering at the
notch point. To handle the statistical precision of estimates, we implement a bootstrapping
procedure with replacement to calculate the standard errors of eR, b, and WRU. In each
estimation, we carry out 100 random resamplings.
The previous identifying method relies on two key assumptions. First, it supposes that
the wealth distribution does not present peaks in the absence of the notch point. As we see
in Section 4, the observation of a well-behaved wealth distribution before the introduction
of the corporate wealth tax allows us to trust on this assumption. Second, it supposes that
the observed excess bunching mass matches the missing mass. This assumption could be
violated if some firms that originally disclosed wealth above WR∗ respond extensively to the notch introduction. For instance, some companies could disappear because of the notch.
Nevertheless, as long as a high reduction of reported wealth is excessively expensive, we
expect that this type of extensive responses is unlikely.
Compared with the panel data methods widely used in the ETB literature, the main
advantage of our estimation method is that we do not have to address the endogeneity issues
effective tax rate. More concretely, a regression with wealth as the independent variable
and an effective tax rate measure as the dependent variable presents endogeneity since both
variables are affected by the non-observable changes in the wealth distribution over time.17
4
Data
For the empirical analysis, we employ the financial statements on the 31st of December
reported by firms to the Colombian Superintendency of Corporations in the period 2003–
2011. Since the corporate wealth tax is charged on the net worth of the 1st of January, for
each tax year we use the value recorded on the 31st of December of the preceding year. For
example, in 2004 we consider the wealth reported on the 31st of December 2003.
The sample composes of large firms measured in assets or income.18 Besides, the financial
data reported to the Superintendency could differ from the fiscal wealth reported to the
Colombian national tax authority due to the disparities in calculation methodologies and the
incentives that firms might face for signaling certain performance to the public. We expect,
however, that these issues attenuate when companies are under surveillance.
Table 2 presents the main descriptive statistics of wealth, assets, liabilities, and pre-tax
profits for the complete sample19 (Column 1) and the restricted sample (Column 2) used in
estimations. As the high standard deviation and the difference between the mean and the
median indicate, the distribution of wealth presents high dispersion and asymmetry.20 Due
to this, when analyzing and comparing the complete and restricted samples, we focus on the location statistics quartile 1 q1, median, and quartile 3q3 of the former sample.
Column 2 of Table 2 reports the descriptive statistics of the firms on which our estimations
are based. It shows the mean and the standard deviation of wealth, assets, liabilities, and
pre-tax profits of those companies that recorded wealth at a distance less than 1,500 million
pesos with respect to the relevant notch point.21 Data indicate that, besides concentrating
on firms with high levels of wealth, our analysis focuses on big-size firms measured in assets
and profits. The average net worth in the restricted sample is 2,158 2004 million pesos.
17See Weber (2014) for a detailed discussion.
18The legal criteria defining the companies that are under surveillance of the Colombian Superintendency
can be found in articles 83 and 85 of Law 222/1995 and in Decrees 3100/1997, 4350/2006, 2300/2008, 2669/2012, and 1219/2014.
19To reduce the influence of extreme values, for the entire sample we exclude the top 0.05% of the wealth
distribution. However, this does not affect estimations since, for them, we use the restricted sample.
20These characteristics also hold in the distribution of assets, liabilities, and pre-tax profits.
21For instance, for the period 2003–2005, Column 2 takes into account those firms with wealth between 1,500
According to Column 1, this value is close to the quartile 3 of the wealth distribution. On
the other hand, the average of assets and liabilities points out that the firms under analysis
are close to the 75-quantile of these variables. Finally, the mean of profits in the restricted sample is 262,001 million pesos, a value also close to this variable’s q3.
Table 2: Descriptive Statistics (1,000s 2004 pesos)
Distance from the Wealth
Complete Sample Notch Point≤1,500 million pesos
(1) (2)
Wealth
q1 250,726
Median 830,555
q3 2,773,814
Mean 4,886,425 2,158,464
Standard Deviation 16,300,000 724,368
Assets
q1 684,587
Median 2,026,205
q3 6,021,728
Mean 9,311,888 5,079,687
Standard Deviation 30,000,000 6,409,553
Liabilities
q1 244,549
Median 791,695
q3 2,656,608
Mean 4,428,483 2,922,170
Standard Deviation 18,200,000 6,299,099
Pre-Tax Profits
q1 5,723
Median 60,527
q3 270,078
Mean 514,373 262,001
Standard Deviation 5,929,713 1,096,658
Observations 175,998 36,989
Notes: Descriptive statistics in 1000s 2004 pesos. Theq1 andq3 values are the quartile 1 and
quartile 3, respectively. The reported number of observations refers to the wealth variable. Column 1 shows the statistics of the complete sample, while Column 2 restricts the sample to companies that reported wealth at a distance from the relevant wealth cutoff less than or equal to 1,500 million pesos. Source: Author’s elaboration based on the Superintendency of Corporations’ data.
As commented in Section 3, one of the assumptions of our identification method for
the elasticity is that, in the absence of notch, the wealth distribution behaves smoothly.
Considering that the 2003 reform introduced the taxation of corporate wealth, we expect to
observe a wealth distribution without bunching at the notch points before 2003. Figure 3
compares the corporate wealth density around the 3 2004 billion pesos threshold during the
period 1995–2001 (black-dashed line) with the one observed in 2006 (blue line). According
to the Figure, there is no bunching in the pre-tax density. Indeed, the dashed-vertical lines
study for years 2004, 2007, and 2011. Notice that the pre-tax wealth distribution behaves as
a smooth function around these values. Furthermore, in 2006 the wealth distribution has an
excess bunching mass at the notch point as the theory and identifying method predict.22
Figure 4: Pre-Tax Wealth Density
2004 2007 2011
0
5
.0
0
0
e
-0
7
1
.0
0
0
e
-0
6
D
e
n
si
ty
1000000 2000000 3000000 4000000 Wealth (1000s 2004 pesos)
1995-2001 2006
Notes: Densities smoothed with kernel method. Source: Author’s elaboration based on Superintendency of Corporations’ data.
5
Main Results of Elasticity and Bunching
Figure 5 presents the main estimation results of the counterfactual distribution, the bunching
degreeb, the wealth of the marginal bunching firmWRU, and the elasticity eR. Given the
cur-vature of the observed distribution, we employ a 5-degree polynomial for the counterfactual extrapolation. The vertical-dashed lines depict the notch point WR∗ as well as the excluded interval of wealth affected by the notch [WL
R, WRU]. Standard errors calculated by the
boot-strapping procedure described in Section 3 are in parenthesis. Panel (a) shows the results
for the 2003 reform, Panel (b) displays the findings concerning the 2006 reform, and Panel
(c) plots the estimates for the 3 billion pesos threshold defined by the Tax Law 1370/2009
and the Decree 4825/2010.
The Tax Law 863/2003 introduces the wealth tax for the period 2004–2006, with a tax
rate of 0.3% for those companies owning wealth above 3,000 billion pesos. The results indicate
that companies do not bunch at the notch point of this institutional setting, implying a b
equals zero. As a result, the elasticity estimate is also zero (Figure 5, Panel a).23
Despite the Tax Law of 2003 implements the taxation of wealth as a transitory measure,
22There is a similar pattern when comparing the pre-tax density to the 2010 density, which has in force the
3 billion pesos cutoff deployed by the 2009 reform and Presidential Decree of 2010.
23This does not mean that the true population elasticity is zero since companies can respond individually to
the 2006 reform reintroduces the tribute and increases the tax rate. As unraveled by Figure
5, Panel (b), this tax scheme generates incentives for bunching. Further, above the cutoff
there is some missing mass of firms. The absence of a big hole in the frequency distribution of wealth reflects the presence of heterogeneity in companies’ responses and frictions.
The findings concerning the 2006 reform are the following. At first, the estimate of the
bunching degree b is 0.357, with a standard error equals 0.106. Thus, with a t-statistic of
3.368, we reject the null hypothesis of no bunching at a 1% significance level. The above
indicates that we witness 35.7% more companies than what we would observe without the
tax notch. Second, the wealth of the marginal bunching firm (the one that most adjusts
its behavior in the presence of taxation) is 3,450 million pesos (standard error of 189.618
million pesos). Therefore, this type of firm depresses its recorded wealth by 15% (450/3,000)
because of the 2006 reform’s notch. Third, the estimated elasticity is 0.250, implying that a 1% raise in the net-of-tax rate triggers an increase of 0.250% in the net worth reported
by the marginal bunching firm. However, with a standard error of 0.271, the elasticity
estimate is not statistically different from zero at a 5% significance level, which may obey to
the noise in the frequency distribution of the Superintendency’s sample. Indeed, as argued
by Saez (2010), Chetty et al. (2011), and Kleven and Wassen (2013), for the utilization of
the bunching methods, it is preferred to obtain the population data of taxpayers since it
attenuates the volatility of the observed distribution and augments the statistical power of
estimates.
The bunching found for 2006 contrasts with the lack of response to the 2003 reform. We offer three possible explanations for these phenomena. First, the 2006 reform’s notch
represented a more considerable tax incentive. According to the model stated in Section 3,
companies do not bunch when the cost of moving is higher than the benefit of a lower rate.
Thus, compared to the moderate tax rate of the 2003 reform, the higher tariff associated
with the 2006 reform would be generating more incentives for bunching.
The dynamic inconsistency of the Colombian government could also explain the
discrep-ancies in the behavioral reactions of firms. As mentioned, the government introduced the tax
as a transitory measure. However, the credibility of this announcement was compromised
when the policy extended for further periods, which could have triggered the responses in
the following years.
Finally, the absence of bunching in 2003–2005 could be due to the initial purpose of the
policy. In its roots, the funds obtained by the corporate wealth tax were going to afford
the fighting against the guerilla groups of the country. At the same time, in these years
the presence of the civil conflict in Colombia had reached high historical levels. Therefore,
Figure 5: Observed and Counterfactual Distributions of Wealth
W* R = WUR
WL R
b = -0.028(0.048) eR = 0.000(0.382)
0 50 100 150 F re q u e n cy
1500 1750 2000 2250 2500 2750 3000 3250 3500 3750 4000 4250 4500 Wealth (1,000,000s 2004 pesos)
Observed Counterfactual
(a) 2003–2005
W* R
WL
R WUR
b = 0.357(0.106) WU
R = 3450(189.618)
eR = 0.250(0.271)
0 20 40 60 80 F re q u a n cy
1500 1750 2000 2250 2500 2750 3000 3250 3500 3750 4000 4250 4500 Wealth (1,000,000s pesos)
Observed Counterfactual
(b) 2006
W*R
WLR WUR
b = 0.238(0.105)
WU
R = 3350(285.796)
eR = 0.447(1.501)
20 40 60 80 100 F re q u e n cy
1500 1750 2000 2250 2500 2750 3000 3250 3500 3750 4000 4250 4500 Riqueza (1,000,000s pesos)
Observada Contrafactual
(c) 2010
Notes: Observed and counterfactual distributions. Wealth in million pesos. Bins width of 25 million pesos. Estimating counterfactual with
5-degree polynomial, eliminating the notch effect in [WL
R, WRU]. The pointWRLis determined visually. The estimate ofWRUis made by the process
described in Section 3. The bunching degreebequals ˆBover the counterfactual distribution. ElasticitieseRcalculated with (5). Standard errors
in parenthesis calculated with 100 resamplings with replacement. The dashed-vertical lines showWRL,WR∗, andWRU. Source: Author’s elaboration
insecurity experienced during that time.
According to Figure 5, Panel (c), the Law and Decree defining the 3 billion pesos threshold
of 2010 induce an excess bunching mass at this point and some missing mass to its right. According to the findings, in 2010 we observe 0.238 times the counterfactual distribution
(standard error of 0.105), so there are 23.8% more firms at the 3 billion pesos cutoff. The
wealth response estimate is 350 million pesos, indicating that the marginal bunching firm
reduces its wealth by 11.7%. Finally, the implied elasticity is 0.447. Nevertheless, with a
standard error of 1.501, this elasticity is not precisely estimated, which could be due to the
noisy distribution presented in 2010.
Notice also that in 2010 there is no gathering of firms at the 2 billion pesos threshold,
which might relate to the moderate tax rate jump at this point. Regarding the 1 billion pesos
notch point, even though we observe a peak in this value, the bunching degree, the elasticity estimate, and the wealth of the marginal bunching firm are not statistically significant, so
that we can not be conclusive.24 Finally, there is too little amount of observations at the 5
billion pesos threshold, which does not allow us to conduct the analysis.
Appendix B applies robustness checks on the econometric specifications used in Figure
5 and conducts placebo tests to assess the validity of the empirical method carried out. In
general, the baseline results presented in this Section perform well when robustness exercises
are implemented. Moreover, the placebo tests suggest that the method employed does not
identify behavioral responses when it should not.
6
The Anatomy of the Behavioral Response
The previous Section proves that firms reduce their wealth as a consequence of the notches
introduced by the wealth tax. This part of the paper inquires about the nature of the
response. Do firms depress their assets or profits because of the tax? Or do they increase
their liabilities? To tackle these questions, this Section conducts a difference-in-differences
analysis in the spirit of Seim (2017) but considering instrumental variables aimed at reducing
the bias generated by the manipulation of treatment. The empirical strategy compares firms
located just below the notch point to those just above, after and before the introduction of the wealth tax.
LetYitbe the variable of interest reported by firm iin yeart. Yit can be the firm’s assets,
liabilities, or pre-tax profits. Following a framework similar to Weber (2014), we model the
log of Yit as
lnYit =αt+γ·Dit+ lnµit+ lnvit+ lnci, (7)
where Dit is a dummy equals 1 if the firm’s wealth is higher than the cutoff in the year
when the tax is in force and t is higher than or equal to the year of implementation, ci is
the non-observable individual heterogeneity, αt is a time fixed effect, and lnµit,lnvit are,
respectively, the permanent and transitory values of lnYit absent wealth taxation.
We propose a difference-in-differences with instrumental variables (DiD-IV) approach to
identify γ, the percentage effect on Y of a discrete jump in the tax rate at the notch point.
We differentiate equation (7) in time
∆ lnYit= ∆αt+γ·∆Dit+ ∆ lnµit+ ∆ lnvit (8)
to control the non-observables embodied in ci and use an instrumental variable for ∆Dit to
control the sorting induced by the reaction of firms to the policy. The instrument is the
treatment status defined by the wealth reported one year before the approval of the tax
reform. For example, when we analyze the 2006 reform, we use the treatment status defined
by the wealth filed in 2005.
We estimate equation (8) separately for the both 3 billion pesos notch points defined in
2006 and 2010.25 In equation (8) differences at time t are s−year differences from t−s tot.
To define the span of the difference, we first compare the year before approval to the time
when the wealth tax is in force (e.g., 2008 vs. 2010 for the tax environment defined by the Tax Law of 2009 and the 2010 Decree). Second, to assess if the effect found in the year
of implementation endures over time, we compare the year prior reform to the year after
implementation (e.g., 2005 vs. 2007 for the 2006 reform).26
Since we are interested in the effects of the tax rate change at the cutoff, we need to
compare similar firms. Therefore, the proposed DiD-IV strategy relies on a selection of the
bandwidth that defines which firms are under analysis. Our baseline specification selects
companies that are 0.750 billion pesos above or below the cutoff. As discussed in Appendix
B, marginal increases and decreases of the bandwidth do not affect the main results.
The DiD-IV strategy rests on the parallel trends assumption to successfully uncover the parameter of interest γ. That is, the selection into treatment defined by the instrument
has to be independent of the changes in the permanent and transitory components of the
outcome variable ∆ lnµit,∆ lnvit.
The arbitrariness of the wealth thresholds mandated by the government implies in
prin-ciple that firms just above do not experience, on average, different changes in their outcome
25Recall that we do not find statistically significant effects on the 1 and 2 billion pesos thresholds deployed
by the government in 2010.
26We do not extend further the analysis to subsequent periods because the introduction of new tax reforms
variables compared to those located just below. Figure 6 allows us to investigate this
reason-ing graphically. It plots the average trends of the log of assets, liabilities, and profits for the
control and treatment group as defined by the instrumental variable. Figures located at the left depict the tendencies for the 2006 reform, while figures to the right display the trends
for the groups defined by the tax regime of 2010.
Based on a visual inspection, we can conclude that the instrument defines a sound
coun-terfactual group for assets and liabilities.27 Regarding pre-tax profits, the assumption seems
plausible for the tax environment implemented in 2010. By contrast, years 1991–2000 and
2002–2004 posit doubts to the parallel trends assumption for the 2006 tax reform. Appendix
B, however, offers more compelling statistical evidence pointing at the validity of the
identi-fication method. More concretely, it implements regression (8) the year before the beginning
of the exercises. This sensitivity analysis does not identify any effect of the treatment before the introduction of the reforms.
Nonetheless, to diminish possible biases in γ and to test the robustness of results, we
implement different controls. First, we include sectorial fixed effects. Second, we evaluate
how do these estimations perform when a variety of specifications aimed to capture transitory
shocks in the outcome variable are implemented.28 We study one specification considering
lnYit−s instrumented with its second lag. Afterward, we consider other specification that
includes ∆ lnYit−s instrumented with lnYit−2s.
Table 3 shows the regression results of equation (8). The top panel reports the findings
concerning the 2006 reform, and the bottom panel records the results regarding the Tax Law of 2009 and the 2010 Decree. Robust standard errors are in parenthesis. Since the
number of observations depends on the outcome variable, the table displays the minimum
quantity.29 Although not reported, all first-stage regressions are statistically significant,
indicating the relevance of the instruments employed. Column 1 shows the results for the
baseline regression, which only considers sectorial fixed effects. Columns 2 and 3 report
the results for the specifications adding separately lnYit−s and ∆ lnYit−s, instrumented with
lnYit−2s.
Results allow us to draw four main conclusions. First, according to the findings of 2006
and 2010, wealth tax rate changes at the notch point cause a reduction in assets the year
when the levy is charged. The negative effect on assets ranges between 5.5% and 6.7% in 2006, and between 13.7% and 17.0% in 2010. Second, firms allocate efforts to cut profits.
27If the graphical analysis is carried out over the groups defined by the variableD, there is a similar pattern.
28In the empirical literature about the ETB, it has been shown that results can be very sensitive to the
specifications used to control for transitory shocks in the outcome variable. Therefore, it is key to test robustness. For a discussion, see Weber (2014) and Kleven and Schultz (2014).
29In all cases this coincides with the number of firms that reported positive profits in the two years under
Figure 6: Trends of Treated and Control Firms 15 15.2 15.4 15.6 A ve ra g e L o g o f Asse ts
1999 2001 2003 2005 2007 Year
Treatment group Control group
14.8 15 15.2 15.4 15.6 A ve ra g e L o g o f Asse ts
2002 2004 2006 2008 2010 Year
Treatment group Control group
(a) Assets 13.8 14 14.2 14.4 14.6 A ve ra g e L o g o f L ia b ili ti e s
1999 2001 2003 2005 2007 Year
Treatment group Control group
13.7 13.8 13.9 14 14.1 14.2 A ve ra g e L o g o f L ia b ili ti e s
2002 2004 2006 2008 2010 Year
Treatment group Control group
(b) Liabilities 12 12.2 12.4 12.6 12.8 A ve ra g e L o g o f Pre -T a x Pro fit s
1999 2001 2003 2005 2007
Year
Treatment group Control group
11 .8 12 12.2 12.4 A ve ra g e L o g o f Pre -T a x Pro fit s
2002 2004 2006 2008 2010
Year
Treatment group Control group
(c) Pre-Tax Profits
The effect is close to 37.7% in 2010 and fades in 2011. The tax environment deployed by
the 2006 reform, on the other hand, is associated with a reduction in profits of around 22%.
Third, there is no robust positive effect on the liabilities recorded by firms. Finally, when statistically significant effects are found through specifications, the coefficient estimates are
highly consistent, pointing at the robustness of the baseline regression.
Table 3: Anatomy of the Behavioral Response
(1) (2) (3)
Panel (a): 2006 Reform
2006
Assets -0.0669*** -0.0560*** -0.0549***
(0.0208) (0.0216) (0.0204)
Liabilities 0.060 0.116* 0.123*
(0.064) (0.0622) (0.0689)
Pre-Tax Profits -0.189* -0.194** -0.205*
(0.102) (0.0967) (0.110)
Observations 849 658 658
2007
Assets -0.129** -0.0564 -0.101*
(0.0511) (0.0528) (0.0542)
Liabilities 0.001 0.0424 0.0288
(0.103) (0.108) (0.115)
Pre-Tax Profits -0.294** -0.228* -0.253*
(0.134) (0.132) (0.141)
Observations 825 553 553
Panel (b): 2009 Reform and 2010 Decree
2010
Assets -0.161*** -0.137*** -0.170***
(0.0353) (0.0393) (0.0377)
Liabilities 0.0431 0.0032 0.0661
(0.0977) (0.0989) (0.118)
Pre-Tax Profits -0.396*** -0.377** -0.354**
(0.145) (0.165) (0.151)
Observations 1,375 1,165 1,165
2011
Assets -0.139*** -0.0977 -0.124**
(0.0514) (0.0647) (0.0562)
Liabilities 0.197* 0.130 0.123
(0.107) (0.112) (0.114)
Pre-Tax Profits -0.341** -0.225 -0.219
(0.173) (0.196) (0.187)
Observations 1,321 819 819
Time FE Yes Yes Yes
Sectorial FE Yes Yes Yes
lnYit−s No Yes No
∆ lnYit−s No No Yes
Notes: Robust standard errors in parenthesis. Sectorial FE is a set of 6 dummies. The treatment indicator is instrumented based on the wealth reported one year before the
ap-proval of the reform. The controls lnYit−2s, ∆ lnYit−sare instrumented with lnYit−2s.
The minimum number of observations is reported. ***p<0.01, ** p<0.05, * p<0.1.
7
Revenue and Efficiency Effects
Based on the results obtained in Sections 5 and 6, this part of the paper derives and calculates
the tax formulas that allow us to address the effects of corporate wealth taxation on revenue
and efficiency. The exposition follows closely Saez et al. (2012) but extends the model to the
analysis of the corporate wealth tax. Since in applying the formulas we use the estimates
identified near the 3 billion pesos cutoffs, our calculations correspond to the effect on large
taxpayer firms measured in wealth, assets, and profits. The equations derived do not match accurately the impacts on those companies that bunch at the notch point as for them the
tax rate change is discrete.
To evaluate the impact of the corporate wealth tax on fiscal funds, define the revenueR
obtained from a firm asτ·WR+E, whereE refers to the sources obtained from other levies.
An increase in τ has two effects on R. First, without taking into account firm’s reactions,
there is a positive mechanical effect raising revenue. Second, there is a behavioral response
that depresses it due to firms modify their behavior because of the higher tax rate. Hence,
the total effect on revenue dRdτ is the sum of the mechanical effect dMdτ =WRand the behavioral
effect dBdτ = dWR
dτ ·τ+ dE dτ:
dR dτ =
dM dτ +
dB
dτ . (9)
A fiscal externality is a secondary effect that the reporting response of corporate wealth
triggers into another tax base. If these externalities do not manifest, the estimate of the
elasticity is a sufficient statistic that summarizes the behavioral response of firms to the tax-ation of wealth. The analysis based solely on this parameter, however, could bias the actual
impacts on fiscal revenue and efficiency when the wealth tax is affecting other components
of fiscal funds.
In the context we are studying, some firms could transfer wealth to their owners in order
to pay fewer taxes. As long as the amount transferred is subject to another tax rate, the
elasticity would be overstating the effects of taxation. Nevertheless, in the period of study,
the wealth tax design differentiates neither the tax rates nor the notch points depending on if
wealth is disclosed by the company or the owner. Therefore, these kinds of fiscal externalities
are not plausible, since no incentives are triggering them.30
A more feasible scenario is that the taxation of corporate wealth could have adverse effects
on reported profits, and Section 6 demonstrated it.31 In consequence, we first find the tax
30Note that the firm may transfer some wealth to the owner to reduce its reported wealthWR. The important
thing is that this transfer does not translate into a new source of fiscal income for the government. Given that the tax system is the same if wealth is declared by the company or the owner, there are no incentives for transferring wealth once the agents have reached the wealth cutoff.
formulas under the assumption of no fiscal externalities as lower bounds. Afterward, we
propose tax equations taking into account the effect of wealth taxation over the corporate
income tax and use them as upper bounds.
Absence of Fiscal Externalities
The assumption of no fiscal externalities implies dEdτ = 0. Hence dBdτ can be expressed as a function of the elasticity:
dB
dτ =−e·WR· τ
1−τ. (10)
Combining equations (9) and (10), we can express the change in revenue dR as a fraction of
the mechanical increase dM depending on the elasticity:
dR
dM = 1−e· τ
1−τ. (11)
This equation shows the relevance of the elasticity when evaluating the effects of tax changes
on revenue. If the firm does not diminish its net worth, the elasticity is zero, and the effect
on revenue equals the mechanical effect, i.e., dR = dM. In this scenario, increasing the tax
rate does not deteriorate the government’s fiscal income. In contrast, ife >0, raising the tax
rate does not translate into an increase in revenue equal to the mechanical projection dM.
The above is summarized in−dB
dM, which from equations (9) and (10) is
− dB dM =e·
τ
1−τ =L. (12)
Expression (12) offers a lower bound L of the impact of the corporate wealth tax on fiscal
funds.
Fiscal Externalities on the Income Tax
In the period of study, the corporate income tax in Colombia was not progressive, and it
established the same statutory tax rate for almost all firms. Let τc and Π be the corporate
income tax rate and the firm’s pre-tax profits, respectively. Considering externalities in Π,
dE dτ =τc·
dΠ
dτ =−τc·γ
Π·Π, (13)
where γΠ = −dΠ
dτ ·
1
Π is the percentage decline in profits due to a marginal increase in the statutory tax rate on wealth τ.
