ARTÍCULOS ORIGINALES
E-ISSN 2389-8194
Vol. 12, No. 1
Enero-junio de 2025
doi: https://doi.org/10.16967/23898186.926
pp. 23-38
rpe.ceipa.edu.co
* Doctora en Economía y Empresa. Universidad Autónoma de Sinaloa, Sinaloa, México. E-mail: yurikoherrera@uas.edu.mx. ORCID: 0000-
0001-9301-9285. Google Scholar: https://scholar.google.com/citations?user=aAmcY2QAAAAJ&hl=es.
** Doctor en Ciencias Económico-Administrativas. Universidad Autónoma de Sinaloa, Sinaloa, México. E-mail: irvin.soto@uas.edu.mx.
ORCID: 0000-0003-2404-4027. Google Scholar: https://scholar.google.com/citations?user=sPzkyosAAAAJ&hl=es. Scopus Author ID:
https://www.scopus.com/authid/detail.uri?authorId=55560147600.
Environmental Indicators as Proxies for
Corruption: An Econometric Approach to
Economic Growth in Mexico
Abril Yuriko Herrera Ríos*
Irvin Mikhail Soto Zazueta**
E-ISSN 2389-8194
Vol. 12, No. 1
Enero-junio de 2025
doi: https://doi.org/10.16967/23898186.926
COMO CITAR ESTE ARTÍCULO
How to cite this article:
Herrera, A.Y. y Soto, I.M. (2025).
Environmental Indicators as
Proxies for Corruption: An
Econometric Approach to
Economic Growth in Mexico.
Revista Perspectiva Empresarial,
12(1), 23-38.
Recibido: 12 de 03 de 2025
Aceptado: 20 de junio de 2025
ABSTRACT Objective. Evaluate the relationship between corruption and environmental
indicators, specically tree density and the Normalized Dierence Vegetation Index, in
Mexico’s states. Methodology. A Ridge Regression with Cross-Validation was applied to
mitigate multicollinearity and correct endogeneity. The dataset includes economic and
environmental data from 32 states in Mexico. Results. Results show that tree density is
negatively correlated with economic activity, while Normalized Dierence Vegetation Index
has a marginally positive impact. These ndings suggest that deforestation may be driven
by economic and governance factors, highlighting the role of environmental degradation
as a corruption proxy. Conclusion. This work contributes to institutional economics by
providing empirical evidence for sustainable public policy design and enhancing corruption
measurement through environmental indicators.
KEY WORDS Corruption, Economic growth, Forest density, Vegetation index, Sustainable
development.
Los indicadores ambientales como variables proxy de la corrupción: un enfoque
econométrico del crecimiento económico en México
RESUMEN Objetivo. Evaluar la relación entre la corrupción y los indicadores ambientales en
los Estados mexicanos, con especial énfasis en la densidad arbórea y el índice de vegetación
de diferencia normalizada. Metodología. Se aplicó la regresión de cresta con validación
cruzada para mitigar la multicolinealidad y corregir la endogeneidad. El conjunto de datos
incluye información económica y ambiental de 32 Estados mexicanos. Resultados. Los
resultados revelan que la densidad arbórea está negativamente correlacionada con la
actividad económica; mientras que el índice de vegetación de diferencia normalizada
presenta un impacto marginalmente positivo. Estos hallazgos sugieren que la deforestación
puede estar impulsada por factores económicos y de gobernanza, lo que pone de relieve
la degradación ambiental como indicador de la corrupción. Conclusiones. Este estudio
contribuye al campo de la economía institucional al proporcionar evidencia empírica para
el diseño de políticas públicas sostenibles y para mejorar la medición de la corrupción
mediante indicadores ambientales.
PALABRAS CLAVE corrupción, crecimiento económico, densidad forestal, índice de
vegetación, desarrollo sostenible.
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ARTÍCULOS
ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
Indicadores Ambientais como Proxies para Corrupção: Uma Abordagem
Econométrica para o Crescimento Econômico no México
RESUMO Objetivo. Avaliar a relação entre corrupção e indicadores ambientais nos
estados mexicanos, com foco na densidade florestal e no índice de vegetação por
diferença normalizada. Metodologia. A regressão Crest com validação cruzada foi
aplicada para mitigar a multicolinearidade e corrigir a endogeneidade. O conjunto
de dados inclui informações econômicas e ambientais de 32 estados mexicanos.
Resultados. Os resultados revelam que a densidade florestal apresenta correlação
negativa com a atividade econômica, enquanto o NDVI demonstra um impacto
marginalmente positivo. Esses achados sugerem que o desmatamento pode ser
impulsionado por fatores econômicos e de governança, destacando a degradação
ambiental como um indicador de corrupção. Conclusões. Este estudo contribui
para o campo da economia institucional, fornecendo evidências empíricas para o
desenvolvimento de políticas públicas sustentáveis e para aprimorar a mensuração
da corrupção por meio de indicadores ambientais.
PALAVRAS CHAVE corrupção, crescimento econômico, densidade florestal, índice
de vegetação, desenvolvimento sustentável.
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ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
Introduction
Corruption is a structural issue that weakens
governance, distorts economic growth, and erodes
public trust. Its negative impact on economic
performance has been widely studied, yet challenges
remain in establishing causality and generalizing
Mauro (1995) demonstrated that corruption
discourages investment by increasing uncertainty
and transaction costs, leading to slower capital
Similarly, Tanzi and Davoodi (2000) highlighted how
infrastructure projects, diverting resources from
essential services like healthcare and education.
in developing economies, where institutional
(Gupta, Davoodi and Alonso-Terme, 2000).
While corruption is generally viewed as an
obstacle to economic development, some scholars
propose an alternative perspective, commonly
referred to as the “grease the wheels” hypothesis
(Huntington, 1968; Leff, 1964). According to this
argument, in highly regulated environments,
corruption may facilitate economic transactions
However, this view remains controversial, as
more recent empirical studies suggest that any
long-term institutional deterioration, reduced
competitiveness, and deepening inequality caused
by corruption (Dong and Torgler, 2020).
A growing body of research has begun to
and environmental degradation, particularly
deforestation. Weak institutional frameworks
often allow illicit activities such as illegal
logging, unauthorized land use, and regulatory
degradation as a direct consequence of corruption.
Studies have linked governance failures to
weak law enforcement (Burgess et al., 2012; Bakhsh
and Ahmed, 2022). Dell (2010) found that regions
severe environmental damage, highlighting the
role of corruption in shaping ecological outcomes.
ranks consistently low on international corruption
faces severe deforestation, with illegal logging
UNEP, 2020). These environmental issues are often
tied to governance failures; as local authorities
Political clientelism and bribery have been linked
to increased deforestation rates, particularly in
states with high biodiversity and weak institutional
oversight (Brondízio et al., 2021). Given these
dynamics, environmental indicators such as tree
density and the Normalized Difference Vegetation
traditional corruption measures, providing a more
objective, spatially detailed approach to assessing
governance failures.
This study investigates the relationship
between corruption and economic growth in
variables to infer corruption levels. Unlike
traditional studies that rely on perception-based
indices, this approach utilizes satellite-derived
data to capture the indirect effects of corruption
on economic performance. By incorporating these
limitations commonly found in corruption research
while offering new insights into the broader
economic implications of governance failures.
A key methodological challenge in corruption-
growth studies is endogeneity, as corruption
simultaneously. To overcome this issue, this study
applies a Ridge Regression with Cross-Validation
among environmental indicators and corruption
estimates. The model is calibrated using economic
allowing for a comprehensive spatial analysis. This
methodological approach enhances the reliability
of the estimates and strengthens the validity of
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ARTÍCULOS
ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
between corruption, environmental degradation,
tree density is negatively correlated with economic
boost economic performance in some regions. This
supports the idea that corruption-driven resource
effect on economic growth, implying that better
environmental conditions may contribute to
economic resilience. These results reinforce the
need to integrate environmental governance into
economic policymaking, as corruption-related
deforestation poses long-term risks to sustainable
development.
By demonstrating the viability of environmental
contributes to institutional economics and policy
research. The use of satellite-based data offers an
innovative alternative to subjective corruption
indices, improving the empirical assessment of
provide valuable insights for policymakers aiming
to design sustainable development strategies that
balance economic growth with environmental
conservation. Understanding the intricate
linkages between corruption, governance, and
environmental degradation can aid in formulating
more effective anti-corruption strategies while
promoting economic resilience.
The remainder of the article is organized
methodological framework, describing the data
sources, the construction of the environmental
model. The following section reports and discusses
indicators, and economic growth across the
conclusions and outlines their implications for
governance, environmental policy, and sustainable
development.
Methodology
In studying the relationship between corruption
and economic growth, addressing endogeneity is
crucial due to the simultaneous interaction between
these variables, which biases ordinary least squares
variations in corruption that are uncorrelated with
the error term in the growth equation.
Vegetation indices are used as instrumental
relevance. Environmental degradation, such as
damage in poorly governed areas, while Burgess et
al. (2012) show how corruption drives deforestation
through illegal logging. This study uses vegetation
indices, such as the NDVI and tree density, as
instrumental variables to estimate corruption in
environmental factors without being directly
activity may affect land cover, NDVI and tree density
and environmental law enforcement. Actions such
as illegal logging, often linked to corruption, alter
vegetation indices independently of broader
in econometric models by associating them with
governance and policy enforcement rather than
direct economic performance.
High-resolution satellite images, analyzed using
analyses, reducing subjectivity and bias associated
with traditional corruption metrics.
This study utilized satellite imagery to analyze
obtained from the SAS.Planet platform, utilizing
Google Satellite and Bing Satellite services to
evaluate forest cover. Image processing was carried
were collected at a zoom resolution of 14, ensuring
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ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
comprehensive territorial coverage. Images
spanned two reference points (Bing Satellite images
providing a robust basis for comparative analysis,
despite a 5-15% margin of error introduced by
cloud cover. Images were converted to grayscale,
smoothed, and processed using the Canny algorithm
for edge detection, enhancing tree contour visibility.
The calculation of tree density involved
summing the detected tree contours in each image,
providing the total number of trees in each study
using the cv2.contourArea() function. Tree density
was determined by dividing the total number of
detected trees by the total study area for each state
using the formula:
A detailed comparative analysis of tree density
performed, showing that the national density per
square meter decreased by 10% over these two
years. The situation was not uniform across states;
some, like Baja California, Durango, Chihuahua, and
Quintana Roo, managed to increase their density,
Table 1. Comparison of Tree density in 2021 and 2023 by State
State Density
2021
Density
2023
Var
(%)
Aguascalientes 8.2457 6.8562 -16.9%
Baja California 5.0251 5.5610 10.7%
Baja California Sur 4.0620 3.0537 -24.8%
Campeche 3.3624 3.1001 -7.8%
Coahuila de Zaragoza 3.1977 2.4336 -23.9%
Colima 4.4537 2.8312 -36.4%
Chiapas 2.6991 2.6865 -0.5%
Chihuahua 6.3107 6.5838 4.3%
Mexico City 8.4206 7.8668 -6.6%
Durango 6.6240 6.9225 4.5%
Guanajuato 5.5866 4.8606 -13.0%
State Density
2021
Density
2023
Var
(%)
Guerrero 3.9341 3.9226 -0.3%
Hidalgo 6.5421 6.4376 -1.6%
Jalisco 5.5234 4.2844 -22.4%
Mexico State 6.3580 6.2963 -1.0%
Michoacán 4.5176 3.2451 -28.2%
Morelos 5.4137 3.9659 -26.7%
Nayarit 5.2565 5.2229 -0.6%
Nuevo León 5.5121 5.0102 -9.1%
Oaxaca 4.1033 4.0352 -1.7%
Puebla 6.7416 6.0398 -10.4%
Querétaro 5.7349 5.0604 -11.8%
Quintana Roo 1.9971 2.0503 2.7%
San Luis Potosí 4.2432 3.8308 -9.7%
Sinaloa 3.4461 3.2900 -4.5%
Sonora 4.7469 2.6100 -45.0%
Tabasco 2.0385 1.6723 -18.0%
Tamaulipas 2.7919 2.1844 -21.8%
Tlaxcala 7.0515 5.9594 -15.5%
Veracruz 2.4453 1.9268 -21.2%
Yucatán 2.0190 1.0424 -48.4%
Zacatecas 5.8656 5.8980 0.6%
Country 4.5896 4.1301 -10.0%
Source: authors own elaboration.
The results in Table 1 show a general decrease
in national tree density by 10% between 2021 and
Durango, Chihuahua, and Quintana Roo, managed
to increase their tree density, with Baja California
decrease of 48.4%, which could be related to
region. These variations highlight the importance
of considering regional and temporal factors when
analyzing the relationship between tree density
and economic growth.
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Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
These variations highlight the importance of
considering regional and temporal factors when
analyzing the relationship between tree density and
economic growth.
The same satellite images used for the tree
density analysis were employed to calculate NDVI
image
acquisition, images were obtained from SAS.Planet,
accessing Google and Bing Satellite services; (ii)
image processing
band corresponds to channel 2 and the NIR band to
channel 1 of the RGB images; (iii) NDVI calculation,
using the standard formula:
where NIR is the near-infrared band and Red
and Baja California.
Figure 1. Examples of Average NDVI for Aguascalientes and Baja California. Source: authors own elaboration.
NDVI and tree density meet the criteria
deforestation and forest degradation, often linked
to illegal logging in regions with weak enforcement
of environmental laws (Burgess et al., 2012).
Similarly, NDVI signals vegetation health and
land use changes tied to corrupt activities, such
as illegal land permits or regulatory evasion (Dell,
that satellite data in Indonesia revealed higher
corruption in areas with severe environmental
degradation. These indicators help isolate the
robust analyses of its impact on economic growth.
(SEMARNAT, 2020). Enforcement varies
significantly across states, with weaker
institutional capacity increasing vulnerability to
illegal logging and corrupt practices (World Bank,
2022). Where oversight is limited, bribery-driven
assumes that weaker law enforcement fosters
corruption-fueled deforestation, justifying the
use of tree density and NDVI to differentiate
between legal and corrupt activities.
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ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
This study applies to the RidgeCV econometric
model to address multicollinearity and enhance
estimation accuracy. This approach is particularly
To optimize the model, cross-validation was
employed, enabling the determination of the
The variables used in the RidgeCV model are
as follows:
(i) ITAEE: The Quarterly Indicator of State
Economic Activity, calculated by INEGI, serves as
on 2018=100, ITAEE captures short-term economic
performance at the state level, aggregating data
enables comparison of economic activity across
states and provides insights into regional economic
(ii) Tree density: These variable measures
often associated with corruption. Studies like
Burgess et al. (2012) demonstrate that corruption
accelerates deforestation, negatively impacting
economic development. By capturing variations in
forest density, this indicator links environmental
corruption to regional economic disparities.
logarithmic transformation of the percentage of
users reporting corruption. The log transformation
normalizes the data, reducing skewness and
capturing the non-linear relationship between
encompasses various corruption-related crimes,
(iv) NDVI: The NDVI, obtained from satellite
imagery, measures vegetation health and density.
It captures the indirect effects of environmental
quality on economic growth, linking vegetation
conditions to agricultural productivity and broader
economic outcomes. Pettorelli et al. (2005) validate
NDVI as a reliable ecological indicator, making it
essential for understanding how environmental
The formulation of the RidgeCV model is as
follows:
where y is the vector of the dependent
X
β are the
In addition, to its ability to regulate the
function that not only minimizes the mean squared
following equation:
, is the mean squared error term, and
is the regularization term that penalizes
This approach ensures that the estimates
obtained are robust and less sensitive to the
correlation between variables, allowing for a better
validation, optimizing the model to minimize the
Initially, socioeconomic indicators like Moderate
were considered as control variables due to their
potential impact on ITAEE. However, their inclusion
introduced multicollinearity with environmental
parsimony and robustness, these variables were
corruption indicators, which proved more relevant
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ARTÍCULOS
ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
The RidgeCV model effectively mitigated
multicollinearity between tree density and NDVI
through regularization, ensuring robust estimates
The validity of NDVI and tree density as
instrumental variables is supported by their
correlation with governance quality and their
dimensions of corruption tied to environmental
malpractices, such as illegal deforestation and
unregulated land use. By leveraging high-resolution
satellite data, this approach ensures robust
inference and minimizes biases associated with
traditional corruption metrics.
Several diagnostic tests were performed
to ensure the robustness of the model: (i)
p-value: 0.20); (iii) autocorrelation, the Durbin-
Watson statistic (1.54) suggested slight positive
autocorrelation, within acceptable limits; (iv)
cross-validation, a 5-fold cross-validation showed
consistent model performance across samples,
and second periods, respectively; (iv) sensitivity
To ensure the robustness of the results and
validate the choice of the RidgeCV model, various
alternative econometric models were evaluated,
The results show that the RidgeCV model offered
presenting the lowest mean squared error and
not capture the relationship between the variables
to handle multicollinearity without eliminating
important variables. This comparative analysis
reinforces the choice of the RidgeCV model for
the study, highlighting its capacity to manage
multicollinearity and provide more accurate and
Results and discussion
The RidgeCV model was used to predict the
effects of corruption on state-level economic
growth. The following results were obtained from
Table 2. RidgeCV Model Results
Metric Value
Average RidgeCV MSE 149.28
Optimal Alpha 35.56
RidgeCV Model Coecients
Tree density -0.469418
log_UCORR 0.807358
NDVI 0.016450
Source: authors own elaboration.
The average cross-validation MSE for the
RidgeCV model was149.28, showing that the model
behaves consistently across different samples. The
of heteroscedasticity, and the Durbin-Watson test
indicated slight positive autocorrelation, but within
acceptable limits.
improvement in prediction accuracy compared to
alternative models, offering valuable insights into
the relationship between corruption, environmental
factors, and economic growth. Cross-validation
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ARTÍCULOS ORIGINALES
ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
the mean squared error and effectively managing
multicollinearity.
(-0.469418) highlights that higher forest cover
economic disparity between rural and urban
regions. Rural areas with dense forests often depend
on agriculture and conservation activities, which
generate lower economic output compared to
industrialized regions. This result also suggests
that deforestation driven by corrupt practices may
temporarily boost economic activity in resource
term sustainability.
corruption may “grease the wheels” of economic
While this challenges the conventional view
of corruption as purely harmful, it highlights
its dual role in regions with weak institutions.
Corruption can facilitate short-term transactions
but ultimately hinders equitable and sustainable
growth in the long run.
(0.016450) links vegetation health with increased
ITAEE, indicating that environmental quality
indirectly supports economic activity through
improved agricultural productivity and ecological
the importance of environmental health in fostering
economic resilience.
The results validate the use of tree density
impact on state-level economic growth. The
negative correlation between tree density and
ITAEE suggests that areas with higher forest
cover, often rural, face governance challenges that
limit economic opportunities. The relationship
between NDVI and ITAEE further demonstrates the
critical role of environmental health in sustainable
economic outcomes, where corruption-driven
deforestation undermines ecological resilience
and long-term growth.
relationships between environmental and economic
tree density and ITAEE suggests that regions with
levels of economic activity as measured by ITAEE.
that this relationship is weak and that other factors
R² = 0,0555
0
20
40
60
80
100
120
140
160
0 2 4 6 8 10
Economic Growth
Tree Density
Figure 2. Comparison of Economic Growth and Tree Density. Source: authors own elaboration.
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ARTÍCULOS
ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
Similarly, the positive relationship of NDVI
suggests that healthier and more abundant
vegetation is associated with greater economic
development in certain states. However, the
correlation remains weak, emphasizing the need
factors for a more accurate interpretation.
ITAEE raises interesting questions about the
dynamics of corruption and economic growth. While
corruption is generally perceived as detrimental to
development, this result suggests that there may
be compensatory mechanisms that mitigate the
R² = 0,0022
0
20
40
60
80
100
120
140
160
0 100000 200000 300000 400000 500000
Economic Growth
Corrup�on (UCORR)
Figure 3. Comparison of Economic Growth and Corruption. Source: authors own elaboration.
The results validate the use of tree density as a
on state-level economic growth. The negative
correlation between tree density and ITAEE
suggests that areas with higher forest cover face
economic disadvantages linked to governance
challenges. Also, the relationship between NDVI and
ITAEE highlights the critical role of environmental
health in fostering sustainable economic outcomes,
demonstrating that corruption-driven deforestation
undermines both ecological resilience and long-
term economic stability.
by Burgess et al. (2012) on corruption and
deforestation, and Dell (2010) on weak governance,
illustrating how corruption mediates the interaction
between environmental degradation and economic
evidence for policymakers to design strategies that
balance economic growth with environmental
environmental harm.
The following are the detailed results of the
RidgeCV model for each state, highlighting how
each variable affects ITAEE in each federal entity:
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ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
Table 3. RidgeCV Model Results by State
State ITAEE 2021 ITAEE 2023 Model Prediction
Aguascalientes 8.24 6.86 7.34
Baja California 5.03 5.56 5.22
Baja California Sur 4.06 3.05 3.25
Campeche 3.36 3.10 3.08
Coahuila de Zaragoza 3.20 2.43 2.51
Colima 4.45 2.83 3.12
Chiapas 2.70 2.69 2.85
Chihuahua 6.31 6.58 6.34
Mexico City 8.42 7.87 8.02
Durango 6.62 6.92 6.77
Guanajuato 5.59 4.86 4.98
Guerrero 3.93 3.92 3.89
Hidalgo 6.54 6.44 6.50
Jalisco 5.52 4.28 4.52
Mexico 6.36 6.30 6.38
Michoacán de Ocampo 4.52 3.25 3.32
Morelos 5.41 3.97 4.05
Nayarit 5.26 5.22 5.15
Nuevo León 5.51 5.01 5.02
Oaxaca 4.10 4.04 4.06
Puebla 6.74 6.04 6.08
Querétaro 5.73 5.06 5.12
Quintana Roo 2.00 2.05 2.12
San Luis Potosí 4.24 3.83 3.90
Sinaloa 3.45 3.29 3.34
Sonora 4.75 2.61 2.75
Tabasco 2.04 1.67 1.71
Tamaulipas 2.79 2.18 2.25
Tlaxcala 7.05 5.96 5.98
Veracruz de Ignacio 2.45 1.93 1.98
Yucatán 2.02 1.04 1.12
Zacatecas 5.87 5.90 5.85
Source: authors own elaboration.
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ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
compared to the actual ITAEE values for the years
us to observe how the independent variables (tree
states showing different trends in their results were
chosen:
shows a decrease in economic activity, although not
as pronounced as observed. The decrease in ITAEE
in tree density, highlighting how this cover can affect
the regional economy.
(ii) Baja California showed an increase in ITAEE,
increase could be associated with the observed
increase in tree density in the state, suggesting
that, in some cases, greater cover could be linked
to improved economic activity.
aligns quite well with reality, suggesting that tree
density and other environmental factors have
a limited impact on this highly urbanized entity.
This reinforces the idea that urban dynamics can
in ITAEE, which model correctly predicts. The
drastic reduction in tree density in Yucatán may
be an important factor in this economic decline,
underscoring the importance of tree cover for
economic activity in certain states.
model can capture regional and temporal variations
in the relationship between environmental factors
and economic growth, providing a valuable tool for
analysis and policy formulation.
illustrate the evolution of the Quarterly Indicator
of State Economic Activity between 2021 and
corruption during the same period. This visual
representation provides valuable insights into
the spatial distribution of economic activity and
Figure 4. Maps of ITAEE Evolution and Users Experiencing Corruption. Source: authors own elaboration.
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Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
A clear regional pattern emerges in the ITAEE
evolution maps. The states in the northern and
central regions show relatively higher economic
activity compared to those in the southern region,
which aligns with national trends indicating
industrial growth and stronger institutional
ongoing industrial development and infrastructure
and Guerrero show minimal growth, underscoring
persistent structural challenges in these regions.
The correlation between economic performance
and corruption perception also reveals interesting
maps suggest a reduction in reported corruption
Veracruz, continue to report high levels. This pattern
is consistent with previous studies indicating that
corruption-related incidents tend to be more
frequently reported in urban areas, where the
concentration of public services, administrative
procedures, and institutional interactions
increases opportunities for corrupt practices
(Drury, Kieckhaus and Lusztig, 2006; Paldam, 2002;
World Bank, 2022).
The spatial comparison underscores the
economic performance, and environmental factors.
high corruption perception (e.g., Veracruz and
impede economic development and increase
vulnerability to corruption; states with moderate
economic growth and lower corruption perception
(e.g., Querétaro and Aguascalientes) highlight areas
with potentially stronger institutional frameworks
that foster sustainable growth; and highly urbanized
with resilient economic performance due to the
These results reinforce the importance of
tailored governance strategies. Public policies
should focus on strengthening institutional
capacity in the southern states while promoting
transparency and accountability in highly urbanized
areas. Integrating environmental and economic
monitoring into governance frameworks can
provide early warnings of corruption and help
mitigate its impact on long-term development.
Conclusion
This study analyzed the relationship between
corruption, environmental factors, and economic
environmental indicators as instrumental variables
to address endogeneity. The results provide robust
for governance quality, offering important insights
regional economic performance.
with rural areas characterized by higher forest
cover. This pattern should be interpreted as a call
for policies that promote sustainable economic
to boost short-term growth. Strategies focused
on reforestation, sustainable forestry, and
ecotourism can create employment opportunities
and contribute to regional development while
preserving environmental resources (Chazdon,
to landowners for maintaining forest cover, could
further enhance these efforts (Pagiola, 2008).
agricultural practices. Promoting agroforestry
and environmentally friendly farming techniques
not only improves vegetation health but also
strengthens local economies. Such initiatives can
enhance resilience to climate change, increase
agricultural productivity, and foster long-term
economic stability in rural regions.
positive coefficient suggests that corruption may
occasionally bypass bureaucratic inefficiencies,
it remains a significant obstacle to institutional
development and equity. Anti-corruption policies
37
ARTÍCULOS
ABRIL YURIKO HERRERA RÍOS, IRVIN MIKHAIL SOTO ZAZUETA
Revista Perspectiva Empresarial, Vol. 12, No. 1, enero-junio de 2025, 24-38
E-ISSN 2389-8194
should focus on increasing transparency and
accountability, with digital solutions such as
e-Government platforms playing a critical role
in reducing opportunities for corrupt practices.
regard.
Environmental education and public awareness
campaigns are equally essential. Incorporating
sustainability into educational programs and
launching initiatives to promote environmental
stewardship among communities can build long-
term support for conservation efforts. Policies
aimed at integrating environmental education at
various levels could strengthen collective efforts to
protect natural resources and promote responsible
development.
The RidgeCV model proved effective in
addressing multicollinearity and improving the
accuracy of the estimates, allowing for a more
precise understanding of the relationship between
economic activity, governance, and environmental
factors. These results contribute to the growing
literature on corruption and economic growth by
introducing a novel methodological approach that
incorporates satellite data and geospatial analysis
into econometric modeling.
While this research provides valuable insights,
indicators, such as water availability, pollution
levels, or governance quality at the municipal level,
to enrich the understanding of regional economic
dynamics. The integration of political factors, such
as election cycles or local political stability, could
also offer a more comprehensive perspective on how
corruption interacts with economic performance.
The evidence presented underscores the
importance of designing public policies that
simultaneously promote transparency, strengthen
institutional frameworks, and encourage
environmental conservation. Balancing these
priorities will be essential for fostering sustainable
economic growth and improving governance in the
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