Income tax and value creation in
Colombian companies
Belky Esperanza Gutiérrez Castañedaa
Universidad de Antioquia
belky.esperanza@udea.edu.co
Daniella Escobar Ortizb
Bancolombia S.A.
daniella.escobar@udea.edu.co
Lorena Vásquez Arango a*
Universidad de Antioquia
lorena.vasquez@udea.edu.co
Tipo: Artículo
de investigación
Recibido:
15 de Enero de 2019
Aceptado:
09 de Mayo de 2019
Abstract
Financial literature has
developed a theoretical framework on business management called Value
Management, this topic has not yet been accounted for economic and monetary
policies as a key factor to establish the convenience and effects of tax
related decisions over business value creation. The aim of the research is to
evaluate the economic and financial impact of income tax on business value
creation of Colombia´s Stock Exchange companies (BVC, “Bolsa de Valores de Colombia” in Spanish) within a five year period (2012-2017). The study was made using
accounting metric tools through the event study methodology allowing to
calculate the Cumulative Abnormal Return (CAR), and
utilizing a multivariate regression model with the dependent variable CAR and
the independent variables EVA,
P/E, ROE and EPS. Income tax policies established during the study
period in tax reforms had neither a direct nor a proportional effect on value
generation.
Resumen
A pesar de que la literatura financiera ha
desarrollado un marco de administración gerencial denominado gerencia del
valor, la política económica no ha integrado el tema como un factor importante
para establecer la conveniencia y efectos de las decisiones en materia tributaria
sobre la creación de valor empresarial. El objetivo de la investigación se
enfoca en evaluar el impacto económico y financiero del impuesto de renta sobre
la creación de valor empresarial de las compañías que cotizan en la Bolsa de
Valores de Colombia durante los años 2012 al 2017. El estudio se realizó
utilizando herramientas contabilométricas por medio de la metodología de
estudio de eventos que permite el cálculo del Retorno Anormal Acumulado (CAR),
además de la utilización de un modelo de regresión multivariable con la
variable dependiente CAR y las variables independientes EVA, P/U, ROE y UPA; encontrando que, en los distintos
escenarios, las nuevas políticas establecidas en el impuesto de renta
sustentado por las reformas tributarias publicadas durante el periodo de
estudio no tienen una relación directa ni proporcional que afecte la generación
de valor de las empresas en Colombia, representado por la muestra de empresas
que cotizan en la BVC.
Palabras clave:
retorno anormal acumulado, impuesto de
renta, bolsa de valores, creación de valor, gerencia de valor.
Keywords:
cumulative abnormal return, income tax, stock exchange, value creation, value
management.
The tax structure in Colombia has a high degree of
instability and complexity in its interpretation, as a result of the fiscal
legislative reforms undertaken (Cárdenas & Mercer, 2005). Evidence of this
is that the Colombian state has implemented 12 tax reforms during the last two
decades; furthermore, it advanced the tax reform called Law 1819 of 2016 as the
last one established in the period 2010-2017
Although Colombian government’s intention with the tax
reform was to guarantee greater tax collection, this led to a generalized
discontent among the major business sectors, since their business value was
threatened
This situation raises questions about the effect on
business value of the income tax established in tax reforms, and it can be
concluded that, whereas the financial literature a management framework called
Value Management has been developed, from
the economic policy perspective, the issue of value in companies has not been
regarded as an important factor to establish the convenience and effects of
economic policy decisions
Hence, interrelations have been generated on the topics of business
valuation and tax burden, embodied in theoretical works by several authors such
as Castilla
In this regard, Boedo
From the above studies, the concept of uncertainty in
tax savings is characterized, since it will not be the same due to decisions
affecting the fiscal legislation, changes in the volume of debt or even losses
in those companies exceeding debt obligations
Under the assumptions of several authors, the importance of the study´s
object in this research is justified. It evaluates companies’ value
from a long-term view, in relation to the impact tax reforms may have on companies’
value generation, taking into account the value drivers; whose foundation is
based on achieving the basic financial aim, since wealth should be distributed
among all the people involved, taking into account good decision-making that
allows to reach this aim
In this sense, the fiscal goal should be in accordance with the value
expected to be obtained in the company; normally, companies need to know their
fair market values in order to know the amount of tax they have
to pay or vice versa. Appraisals to fiscal effects should seriously take
into account the changes in legislation impacting business value, so corporate
strategies should tend for a fiscal planning which allows to maximize the basic
financial aim
Knowing the context and considering that the possible
relationship between tax changes and value generation in organizations has not
been previously studied, we opted to choose Colombian companies as sample for
the study and in this way obtain a first observation, deeper than that of other
authors who have focused only on demonstrating tax savings resulting from being
indebted.
Income tax in the Colombian context
In the
current Colombian legislation, taxes have their support in the constitutional
precept of article 95, paragraph 9° of the Colombian Political Constitution of
1991, according to which a citizen´s duty to contribute towards the State’s
actions; and the taxing faculty lies on the legislative organ of public power,
that is, on the Congress of the Republic, which is responsible for establishing
fiscal and parafiscal contributions (Corte Constitucional,
1991); while the main tax collecting entity is the Tax and Customs Authority
(DIAN, “Dirección de Impuestos
y Aduanas Nacionales” in
Spanish)
In this way, with the aim of regulating tax matters in
Colombia, the Congress of the Republic issues related laws, Tax Statute or
Decree 624 of 1989 being the main one, which is modified through legislative
reforms passed by Congress. These represent the effort of the National
Government to modernize the tax system, consisting of a complete revision of
the tax structure to streamline the tax system and achieve greater tax
collection
As per the
tax income comprised in each tax reform and contained in the Tax Statute, tax
payers are all those natural and legal persons that conduct activities that are
susceptible of increasing their net equity or their wealth, the legal persons
having the condition of being tax filers
The concept and theories of value creation were
studied mainly by Adam Smith, but the theories of Karl Marx, David Ricardo,
John Keynes, among others
In this
way, the so-called Value-based Management, defined by García
Other
measures that enable an approximations to a companies’ valuation are the
so-called multiples, which represent relationships between the market price of
a share and a measure of the economic or accounting value of the business in
terms of each share, among which the most used multiple is the market
price/current earnings relationship (Martín & Trujillo, 2004).
RESEARCH
METHODOLOGY
The development of the study was determined within a
quantitative approach, since it uses“(…) random,
experimental and quasi-experimental techniques, pen and paper “objective” tests,
multivariate statistical analyses, sample studies, etc.” (Cook & Reichardt, 1986); all these focusing on the new
theoretical accounting metrics trend considered as a tool that involves
quantitative, mathematical and statistical methods to solve accounting problems
(Francischetti, Poker & Padoveze,
2017).
In this way, and using accounting metric tools, the
event study method was employed, which evaluates the impact of a given event at
a given date, to evaluate the possible abnormal returns caused by the event
The data selected for the analysis were treated by
means of cross-sectional panel data and, additionally, they incorporate time
series of secular trend since, according to Pindyck &
Rubinfeld
In this way, in order to achieve the research aim, an
initial population of the share prices of 59 companies which are active on the BVC
per year, from 2011 to 2017, is obtained to calculate the dependent variable without
considering the share price as a measure of value. The population criteria
established for each event are subsequently filtered according to:
(i)
stock
movement, excluding companies that are not active on the Stock Exchange for
more than six consecutive days,
(ii)
the
presence of EVA, P/E, ROE and EPS indicators, which become the variables that
evidence value generation,
(iii)
exclusion
of preferential shares, since they generate information duplicity from the
value drivers of the companies,
(iv)
exclusion
of companies belonging to the financial sector, since these businesses are
highly leveraged
(v)
elimination
of zero-data yielded after normalizing the EVA, P/E and EPS variables.
The final sample per year is the following (see Table 1).
Table
1. Sample filtering
Concept |
Event 2012 |
Event 2014 |
Event 2016 |
Initial |
59 |
59 |
59 |
Stock Market
Movement |
-34 |
-35 |
-35 |
EVA |
-2 |
-2 |
-1 |
P/E |
0 |
0 |
0 |
ROE |
0 |
0 |
0 |
EPS |
0 |
0 |
0 |
Preferential
Share |
-4 |
-6 |
-7 |
Financial
Company |
-5 |
-3 |
-3 |
Standardization |
-3 |
-3 |
-3 |
Total sample |
11 |
10 |
10 |
Source: own elaboration.
The standardization of the EVA, P/E and EPS variables was
carried out taking normalization (0.1) into account and eliminating the
different scales presented, transforming the original variable into a similar
one that keeps the same proportions, but taking into account a standard scale
(Cubero & Berzal, w.d.):
(1)
Before the variables regression analysis and taking into account the determination of the impact on the
generation of business value of the income tax established in the tax reforms, this
study departs from the event study methodology as a first approximation to the impact.
With the aim to identify the existing volatility in
the share price of the BVC as an effect of the publication of the tax reforms
during the period 2012-2017, the event study methodology will be used which allows
to determine the effects of an external event on a capital market´s assets
Event windows of 110, 106 and 96 days are considered
for the years 2012, 2014 and 2016, respectively, which were selected according
to the date on which the law was filed in Congress: (04 October 2012 for Law
1607 of 2012, 03 October 2014 for Law 1739 of 2014 and 19 October 2016 for law
1819 of 2016
In this way, starting from the date of the event, 55,
53 and 48 days are considered prior to and after the publication date of Law
1607 of 2012, 1739 of 2014 and 1819 of 2016, respectively; the first event
being 26 December 2012, the second 23 December 2014 and the third 29 December 2016;
periods in which the abnormal returns of the share prices will be analyzed, considering
an estimation window of 180 working days prior to the event window (see Figure
1).
Figure 1. Scheme of event study and estimation window
Source: own elaboration.
Once the event and estimation windows are defined, as
observed in Figure 1, share prices are taken to carry out a normalization
process and determine the basis for the calculation of the cumulative abnormal
returns.
Cumulative
Abnormal Return - CAR
With the aim of determining whether the previously
described events presented volatility in the share prices of the companies that
are or were listed on the BVC during the study period, the cumulative abnormal
return was used as statistical measurement instrument. To this end, the actual
share return is compared with the estimated return, a difference that is called
abnormal return and which, according to Mackinlay
ARi,t = Ri,t
– E[Ri,t / Xt] (2)
where, ARi,t is the abnormal return of share i on date t of the event, Ri,t is the return of share i on date t of the event, and E[Ri,t / Xt] is the expected
return of share i on date t of the event
multiplied by the return. Xt is
the return of market on date t of the event.
Additionally, the following formula is derived from
the previous one:
ARi,t
event = Ri,t event – Rnormal i,t event (3)
where, Rnormal
i,t event is the normal or estimated
return during the event’s window.
The COLCAP reflects the variations in the prices of
the most liquid shares listed in BVC
The following formula is employed in order to
determine the normal returns
Rnormal
i,t event = αi + βi
× Rm,t + εi,t (4)
here, Rm,t is
the profitability of the shares in the market in period t, εi,t is
the random error in the process of generating profitability in period t,
αi
is the intercept, and βi is the coefficient of the slope.
To determine the value of the intercept and that of
the coefficient, a linear regression is performed with the SPSS software, taking
the COLCAP index as dependent variable and each share price of the sample as
independent variable.
Finally, the cumulative abnormal return is calculated,
which corresponds to the sum of the abnormal returns of each share price of the
sample
CARi = i, t event (5)
Where CARi is the Cumulative Abnormal Return of the company,
t1 represents the first
day of the event, and t2 represents
the last day of the event.
After calculating the CAR, a multivariate regression
model is constructed, in which the independent variables are EVA, P/E, ROE and EPS,
which turn out to be the variables that evidence the value generation (see
Table 2) and the dependent variable is the CAR result for each event.
Table 2. Variables
description
Variable |
Description |
Way to Calculation |
CAR |
It represents
the independent variable of the linear regression model; constitutes the cumulative
abnormal return of the shares resulting from the change in tax reforms
concerning income tax. |
Simple linear
regression |
EVA |
Economic
Value added. It represents the final result after
covering all costs, expenses and expected gains or costs of capital. |
EVA= Invested
Capital × (Net asset profit – Weighed average cost of capital) |
P/E |
Price/Earnings
is a multiple that functions as the company’s value
indication and is calculated as the share closing price over the earnings per
share. |
P/E= Share
price / Earnings per share |
ROE |
Returns on
equity show the profitability of invested capital, calculated as the net
profit over equity. |
ROE= Net
profit/Total equity |
EPS |
Earnings per
share is a multiple that shows the net profit obtained over the number of
circulating shares. |
Net profit /
Circulating shares |
Source: own elaboration.
The
indicator of the independent variables of value corresponds to the calculations
with the information related to the financial statements of the year after the
event’s occurrence (2013, 2015 and 2017) since, according to the literature, the
impact of the tax reforms on financial reports and the generation of value
measured with value drivers
Hence,
to meet the research goal and following the characteristics of a quantitative
study, the next research hypotheses are posited, seeking to test them by means
of accounting metric tools:
Hi: The income
tax modifications established by the tax reforms in Colombia do not have an
impact on the business value creation of the companies listed on the BVC.
Ho (Null):
The income tax modifications established by the tax reforms in Colombia do not
have an impact on the business value creation of the companies listed on the
BVC.
With
the aim of determining the significance of the cumulative abnormal returns
derived from the tax reforms, the T-Student statistics was calculated with degrees
of freedom and a probability at a significance level α=0.05 (see Equation 6)
(6)
where
represents the average of abnormal returns,
represents the deviation of abnormal returns
and
is the number of days of the event window.
To
continue with the hypotheses testing and the results analysis, the search for the
financial data of the companies in the sample during a time period between the
years 2012 and 2017 is employed as data collection technique. This information
is collected from the databases of the corresponding Superintendencies,
Bloomberg and corporate information from the respective business website in
terms to obtain the accounting information related to financial statements and
ratios, and the BVC and the Economática software to
obtain market variables.
The
use of different information sources is due to financial markets in Colombia
are considered in the literature as emerging markets and thus information is
limited; as pointed out by Peña, Ortiz & Espitia
RESULTS ANALYSIS AND CONCLUSIONS
To
support the research hypotheses and have a first approximation to the collected
data, a descriptive analysis of each selected variable was performed to
evaluate its behavior and identify atypical data altering the sample average.
Consequently, after characterizing the variables, the correlation analysis of
the study object was conducted to establish, in this case, the impact of the
tax reforms (income tax) on the value generation of the companies that are or
were listed on the BVC in the time period 2012-2017, by means of a multivariate
regression model.
Descriptive analysis of the variables
The
statistical descriptive analysis of the information results from the collection,
ordering, and processing of the data allowing to interpret it and identify the
behavior and nature of the dependent and independent variables, departing from
the analysis of the mean and the deviation present in the statistics of the variables
(see Table 3).
Table
3. Statistics of the variables
Event 2012 |
Event 2014 |
Event 2016 |
|||||||
Variables |
Mean |
Typical
deviation |
N |
Mean |
Typical
deviation |
N |
Mean |
Typical
deviation |
N |
CAR |
0.058 |
0.160 |
11 |
- 0.000 |
0.153 |
10 |
0.024 |
0.130 |
10 |
EVA |
0.157 |
0.288 |
11 |
0.744 |
0.110 |
10 |
0.214 |
0.150 |
10 |
P/E |
0.150 |
0.295 |
11 |
0.229 |
0.278 |
10 |
0.979 |
0.011 |
10 |
ROE |
0.062 |
0.045 |
11 |
0.066 |
0.041 |
10 |
0.074 |
0.063 |
10 |
EPS |
0.082 |
0.065 |
11 |
0.282 |
0.201 |
10 |
0.220 |
0.194 |
10 |
Source: own elaboration based in results from SPSS.
Initially,
and as a first approximation to the impact of the changes in income tax, an analysis
is performed taking as a basis the share price, assuming it not as a measure of
value but as an input to understand whether atypical fluctuations are generated
in per share earnings in the period in which the event was defined. Thus, the
dependent variable CAR measures the cumulative abnormal returns obtained due to
an event that may have an impact on the normal return of a share price and
allows to measure the volatility of the shares, either for their transactional
volume or their price.
During
the studied period, the CAR indicates that the returns expected in the companies
did not observe a significant volatility in face of the tax reforms (see Table 4),
generating an average CAR of 0% for the year 2014, revealing that the event did
not motivate a price fluctuation in the market. Conversely, for the years 2012 and
2016 the result of the CAR yielded a mean of 5.8% and 2.4%, respectively. These
values are not quite significant to claim that the companies that are or were
listed on the BVC presented an abnormal behavior in face of each significant tax
event. This permits to initially conclude that the tax reforms did not
significantly intervene in the normal development of the financial behavior of
the share market price during the study period.
Additionally,
with respect to the independent variables selected for the research, according
to the theoretical antecedents indicating that they are representative at the
time of measuring the generation of business value and according to the results
obtained, the result of the EVA variable is highlighted. For the three analyzed
events, this result indicated that the companies of the sample created value, because
profitability in the business was generated after deducting the total cost of
capital
Similarly,
when conducting the analysis of the atypical observations by means of box-and-whisker
plots for each one of the variables, it was identified that for events 2012,
2014 and 2016, atypical data was obtained. For the case of event 2012, seven
atypical observations occur: four in the EVA variable, two in the P/E variable
and one in the ROE variable. For event 2014 four outliers appeared: two for the
P/E variable, one for the CAR variable and one for the ROE variables. Lastly, for
event 2016, two atypical observations occurred in the EVA variable.
Atypical
observations or data are frequent in the statistical studies dealing with data
related with the analysis of stock markets
Table
4 illustrates the average of the t statistics and the percentage of companies
with a statistics |t_(N-2)|≥3.1824,
at a significance level α=0.05. The
above statistical analyses permit to conclude, prior to proving the model, that
the research hypothesis that there are no abnormal returns derived from the tax
reforms is not rejected, since with the calculation of the 𝑡 statistics it is generally identified that there is
significance in the 2012-2013 and 2016-2017 event windows. Therefore, there are
no cumulative abnormal returns derived from the tax reforms at 100%. However,
for the 2014-2015 event, only 20% of the companies analyzed have significance,
which leads to rejecting the research hypothesis for this case, which indicates
that there was an impact on the share price derived from the tax reform of
2014. That is, the impact of the selected event on the volatility of the share
price is null or little significant. However, this conclusion can only be
confirmed from a global perspective, jointly considering all the variables
under study through the multivariate regression model.
Table 4. Statistics of the variables
|
CAR 2012-2013 |
CAR 2014-2015 |
CAR 2016-2017 |
General |
|
T-Student |
108.318 |
2.735 |
93.714 |
69.548 |
|
Significance percentage |
100.00% |
20.00% |
100.00% |
74.19% |
Source: own elaboration based in results from SPSS.
Multivariate analysis per event for the period 2012 – 2017
The
multivariate analysis helps to analyze and generalize the behavior of the
dependent variable according to how the independent variables behave, besides
helping to explicitly control the factors affecting the dependent variable
After applying a systematic information search, the
results show that no previous study or research on the multivariate regression
model (see Equation 7) has related the two knowledge areas that are the object
of this study. Thus, it can be indicated that the procedure to define the
dependent variable was determined according to the object of study that, in
this case, consists in evaluating the possible impact of disclosing information
from a tax reform on companies’ value generation.
where
i, j indicates the company and the year of
study, respectively.
In
this case, the CAR (cumulative abnormal returns) were used with the aim of
evaluating such impact by means of the event study methodology, which has been
employed in studies evaluating the impact in stock markets in North America,
Europe and Asia
Thus,
to appraise the explanatory power of the multivariate regression model, the R2 coefficient is
evaluated which shows how much of the CAR variance is explained by the independent
variables defined in Table 3. Hence, considering an R2 for each one of the events analyzed at a significance
level of 10%, it is observed that for the case of the 2012 event, the independent
variables explain 52% of the changes in the value of the cumulative normal
returns of the model, for the 2014 event they explain 47%, for the 2016 event
they explain 60%, and for the period 2012-2017 they explain 11% of the changes
in the CAR (see Table 5).
Table
5. Regression model coefficients and significance
Event |
R |
R2 |
Adjusted R2 |
Std. Error |
Durbin-Watson |
F |
Significance |
2012 |
0.72 |
0.52 |
0.19 |
0.14 |
1.56 |
1.60 |
0.29 |
2014 |
0.68 |
0.47 |
0.04 |
0.15 |
1.62 |
1.09 |
0.45 |
2016 |
0.77 |
0.60 |
0.28 |
0.11 |
2.00 |
1.86 |
0.26 |
2012-2017 |
0.33 |
0.11 |
-0.03 |
0.15 |
1.59 |
0.81 |
0.53 |
Source: own elaboration based in results from SPSS.
In
a first moment it can be claimed that a small R2 reflects the difficulty of predicting
results with high accuracy with respect to the changes in the cumulative
abnormal returns, given that when an R2
is close to zero, this means that the independent variables do not explain the
behavior of the dependent variable (Fávero, Belfiore, Lopes & Chan, 2009). However, even though the
explanatory power of the models per event is small, this does not necessarily
indicate that the model employed is little useful or that it does not
adequately explain the analyzed phenomenon. As cited by Gutierrez (2011, p. 98),
Wooldridge points out that a small R2
is typical of studies related to social sciences, in which it is difficult to
anticipate the individual behaviors of the independent variables over the
depending variable. For this reason, the models of the 2012, 2014, 2016 events
and the 2012-2017 period, are reliable in the sense that it can be claimed they
are significant.
To
support the above conclusion, the degree of significance of the regression
model for each one of the events was analyzed, according to a statistical
significance level of 5% (see Table 5). This test intends to prove whether or
not the independent variables explain the behavior of the dependent variable, providing
the result is above the defined 5%
In
this way, the ANOVA (Analysis of variance) in Table 5 presents the results of the
model significance for the three events analyzed and for the set of data
grouped from year 2012 to year 2017. In the case of event 2012, Sig F=0.29>0.05; in event 2014, Sig. F=0.45>0.05; in event 2016, Sig. F=0.26>0.05. For the period 2012-2017,
Sig. F= 0.53>0.05. This means that
none of the independent variables considered in the model is significant to explain
the behavior of the CAR in any of the events proposed, let alone for the
evaluation period.
Likewise,
in the results of the models it can be evidenced that the betas of the
independent variables are generally not significant at 1% and 5% (see Table 6).
The EVAestad coefficient is negative, indicating that
with an additional increase the cumulative returns decrease, given that when
increasing company value, investors will not perceive this in their share
returns; rather, this increase must be compensated via higher income taxes. On
the other hand, the coefficient of the PUest variable
is negative, indicating that in the face of a tax reform, investors are willing
to pay a lower price per share, thus generating lower abnormal returns since
they will obtain lower net profit benefits. ROE and UPAest
variables have a positive coefficient, which is consistent with financial
literature.
Table
6. Model coefficients
Variable |
Non
standardized coefficients |
Typified
coefficients |
t |
Significance |
|
B |
S.E. |
Beta |
|||
(Constant) |
0.065 |
0.061 |
|
1.079 |
0.290 |
EVAestad |
-
0.165 |
0.094 |
-
0.374 |
-
1.747 |
0.092 |
PUest |
-
0.058 |
0.066 |
-
0.175 |
-
0.873 |
0.391 |
ROE |
0.305 |
0.586 |
0.103 |
0.520 |
0.607 |
UPAest |
0.149 |
0.161 |
0.183 |
0.925 |
0.363 |
Source: own elaboration based in results from SPSS.
Similarly,
considering the correlational analysis of the variables (see Table 7), it is
evidenced that they do not have a significant linear relationship with the CAR,
which means that the independent variables of value do not explain the changes
in the CAR resulting from the changes in income tax, based on the assumption of
a linear model.
Table
7. Correlation analysis
|
CAR |
EVA |
P/E |
ROE |
EPS |
|
CAR |
Corr. Pearson |
1.00 |
-0.24 |
-0.05 |
-0.00 |
0.06 |
Sig. |
|
0.19 |
0.78 |
0.98 |
0.74 |
|
EVA |
Corr. Pearson |
|
1.00 |
-0.26 |
0.23 |
0.33 |
Sig. |
|
|
0.16 |
0.21 |
0.07 |
|
P/E |
Corr. Pearson |
|
|
1.00 |
0.18 |
0.04 |
Sig. |
|
|
|
0.33 |
0.85 |
|
ROE |
Corr. Pearson |
|
|
|
1.00 |
0.07 |
Sig. |
|
|
|
|
0.72 |
|
EPS |
Corr. Pearson |
|
|
|
|
1.00 |
Sig. |
|
|
|
|
|
Source: own elaboration based in results from SPSS.
Additionally,
with the help of the SPSS software, the validation tests of the regression analysis
assumptions for the period 2012-2017 are conducted. The aim is to support the
development of the multivariate regression model and evaluate whether the
variables meet the hypothesis of normality, homoscedasticity, autocorrelation
and multicollinearity of the residuals. This was verified with the
Kolmogorov-Smirnov, Pesaran-Pesaran, and Durbin-Watson
tests (see Table 5) and the VIF variables and tolerance analysis (see Table 8),
respectively.
Table
8. Model tests
Premise |
Test |
Statistic |
Sig. T |
Evaluation |
Residuals Normality |
Kolmogorov-Smirnov |
0.44 |
0.99 |
The null hypothesis is accepted for residuals
normality |
Residuals homoscedasticity |
Pesarán-Pesarán |
0.13 |
0.72 |
The null hypothesis is accepted for residuals
homoscedasticity |
Absence of correlation between the residuals |
Durbin-Watson |
1.59 |
- |
Absence of correlation between the residuals |
Multicollinearity of the independent variables |
Maximum VIF-Minimum Tolerance |
1.34 -
0.75 |
- |
Acceptable multicollinearity |
Source: own elaboration based in results from SPSS.
The
results of the tests performed (see Table 8) allowed to validate the
assumptions of the multivariate linear regression model, giving additional
support to the previously shown results. The evaluation of the K-S test yielded
a statistic of 0.44 with a significance of 0.99. According to Corrar, Paulo & Filho
Additionally,
according to the Pesarán-Pesarán test, it is
concluded that the data are not heteroscedastic, that is, the variance of the
residuals is not constant for the independent variables, considering that the
significance of the test is greater than 0.05 (Sig. T = 0.72>0.05). Besides, it is evidenced that there is no
correlation among the explanatory variables of the model, since its result for
the analysis period is equal to 1.59, which is close to two, a value accepted
to confirm the nonexistence of the autocorrelation (Fávero,
Belfiore, Lopes & Chan, 2009).
In
a similar way, autocorrelation tests to the residuals of the model in Equation 7
were conducted by the Breusch-Godfrey test. Table 9 illustrates the results for
each one of the models estimated in the study. In general, the model does not
present autocorrelation of order 1 and 2, given that in each one of the
analyses p-values>0.05.
Table 9. Breusch-Godfrey test for serial
correlation
Model |
Breusch-Godfrey order 1 P-value |
Breusch -Godfrey order 2 P-value |
2012-2013 |
0.57 |
0.053 |
2014-2015 |
0.40 |
0.32 |
2016-2017 |
0.89 |
0.59 |
General |
0.30 |
0.29 |
Source: own elaboration based in results from SPSS.
Lastly,
the multicollinearity of the variables, evaluated with the VIF and the
tolerance, -statistics which are close to the unit- shows that there are no
significant multicollinearity problems among the explanatory variables
invalidating the regression model
DISCUSSION AND CONCLUSIONS
In
conclusion, as evidenced in the statistical analyses and the multivariate
regression model, based on the results obtained, in first place, and taking
into account the CAR calculation, it is observed that the abnormal returns of
share profitability do not present significant alteration resulting from the
modifications in the income tax in the Colombian tax regulation. This result is
confirmed with the analysis conducted with the regression model, which yields
low correlations between the independent variables and the dependent variable.
This assertion is confirmed with the tests of the correlation analysis
assumptions; in this way, the main hypothesis (Hi) posited is not rejected,
which states that income tax does not have an impact on the value generation of
the companies of the sample in the period 2012-2017.
Regarding
the correlational analysis, a low statistical significance was observed between
the CAR as dependent variable and the value generation variables of the
companies included in the accounting metric model. For the present research, this
indicates that the modifications of the income tax established in the tax
reforms between the years 2012 to 2017 in Colombia did not have an impact on
the business value creation of the sampled companies listed on the BVC. In
general terms, changes mentioned in the income tax for such companies do not
lead to substantial modifications, as mentioned by Gómez and Steiner
The
present research is a study that empirically contrasts the financial
theoretical support led by the work of Modigliani & Miller
The
Colombian tax system is particular and changing mainly due to the following
aspects: i) the taxable nature of corporate tax, ii) the
different reasons for deductions and the types of deductions permitted, iii) the
possibility of transferring unused tax deductions to later exercises, and iv) the
tax discounts permitted by law. These aspects generate a different magnitude of
fiscal advantage or disadvantage for each company in
particular. Therefore, the results yielded in the present analysis are
not interpreted as a rejection of the financial theory led by Miller
It
is also important to mention that, with the great amount of reforms taking
place in the country, the big companies have opted to plan their tax issues
with the aim of legally controlling and reducing the tax burdens without
incurring tax avoidance or evasion
Along
this line, highlighting the conceived interdisciplinarity, it is recommended
for future analyses to consider a nonlinear model and evaluate the hypothesis
considered in a Latin American context with the aim of obtaining a greater
sample size. Additionally, it is important to conduct studies to develop joint
work including tax aspects and theoretical financial developments, involving
the value drivers in the analysis of the tax regulation implementation, not
only considering the capital structure and the impact on share price.
ACKNOWLEDGMENTS
We thank the CIC (Centro de Investigaciones y Consultorías) and the Faculty of Economics of the
University of Antioquia for supporting us with the necessary economic resources
to develop this research.
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* Autora corresponsal.
a Universidad de Antioquia, Departamento
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